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AI for Marketing & Growth #1 - Predictive Analytics in Marketing
 
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AI for Marketing & Growth #1 - Predictive Analytics in Marketing Download our list of the world's best AI Newsletters 👉https://hubs.ly/H0dL7N60 Welcome to our brand new AI for Marketing & Growth series in which we’ll get you up to speed on Predictive Analytics in Marketing! This series you-must-watch-this-every-two-weeks sort of series or you’re gonna get left behind.. Predictive analytics in marketing is a form of data mining that uses machine learning and statistical modeling to predict the future. Based on historical data. Applications in action are all around us already. For example, If your bank notifies you of suspicious activity on your bank card, it is likely that a statistical model was used to predict your future behavior based on your past transactions. Serious deviations from this pattern are flagged as suspicious. And that’s when you get the notification. So why should marketers care? Marketers can use it to help optimise conversions for their funnels by forecasting the best way to move leads down the different stages, turning them into qualified prospects and eventually converting them into paying customers. Now, if you can predict your customers’ behavior along the funnel, you can also think of messages to best influence that behavior and reach your customer’s highest potential value. This is super-intelligence for marketers! Imagine if you could not only determine whether a lead is a good fit for your product but also which are most promising. This’ll allow you to focus your team’s efforts on leads with the highest ROI. Which will also imply a shift in mindset. Going from quantity metrics, or how many leads you can attract, to quality metrics, or how many good leads you can engage. You can now easily predict your OMTM or KPIs in real-time and finally push vanity metrics aside. For example, based on my location, age, past purchases, and gender, how likely are you to buy eggs I if you just added milk to your basket? A supermarket can use this information to automatically recommend products to you A financial services provider can use thousands of data points created by your online behaviour to decide which credit card to offer you, and when. A fashion retailer can use your data to decide which shoes to recommend as your next purchase, based on the jacket you just bought. Sure, businesses can improve their conversion rates, but the implications are much bigger than that. Predictive analytics allows companies to set pricing strategies based on consumer expectations and competitor benchmarks. Retailers can predict demand, and therefore make sure they have the right level of stock for each of their products. The evidence of this revolution is already around us. Every time we type a search query into Google, Facebook or Amazon we’re feeding data into the machine. The machine thrives on data, growing ever more intelligent. To leverage the potential of artificial intelligence and predictive analytics, there are four elements that organizations need to put into place. 1. The right questions 2. The right data 3. The right technology 4. The right people Ok.. let’s look at some use cases of businesses that are already leveraging predictive analytics. Other topics discussed: Ai analytics case study artificial intelligence big data deep learning demand forecasting forecasting sales machine learning predictive analytics in marketing data mining statistical modelling predict the future historical data AI Marketing machine learning marketing machine learning in marketing artificial intelligence in marketing artificial intelligence AI Machine learning ------------------------------------------------------- Amsterdam bound? Want to make AI your secret weapon? Join our A.I. for Marketing and growth Course! A 2-day course in Amsterdam. No previous skills or coding required! https://hubs.ly/H0dkN4W0 OR Check out our 2-day intensive, no-bullshit, skills and knowledge Growth Hacking Crash Course: https://hubs.ly/H0dkN4W0 OR our 6-Week Growth Hacking Evening Course: https://hubs.ly/H0dkN4W0 OR Our In-House Training Programs: https://hubs.ly/H0dkN4W0 OR The world’s only Growth & A.I. Traineeship https://hubs.ly/H0dkN4W0 Make sure to check out our website to learn more about us and for more goodies: https://hubs.ly/H0dkN4W0 London Bound? Join our 2-day intensive, no-bullshit, skills and knowledge Growth Marketing Course: https://hubs.ly/H0dkN4W0 ALSO! Connect with Growth Tribe on social media and stay tuned for nuggets of wisdom, updates and more: Facebook: https://www.facebook.com/GrowthTribeIO/ LinkedIn: https://www.linkedin.com/company/growth-tribe Twitter: https://twitter.com/GrowthTribe/ Instagram: https://www.instagram.com/growthtribe/ Snapchat: growthtribe Video URL: https://youtu.be/uk82DHcU7z8
Views: 20852 Growth Tribe
Data Mining using R | R Tutorial for Beginners | Data Mining Tutorial for Beginners 2018 | ExcleR
 
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Data Mining Using R (sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information. Data Mining Certification Training Course Content : https://www.excelr.com/data-mining/ Introduction to Data Mining Tutorials : https://youtu.be/uNrg8ep_sEI What is Data Mining? Big data!!! Are you demotivated when your peers are discussing about data science and recent advances in big data. Did you ever think how Flip kart and Amazon are suggesting products for their customers? Do you know how financial institutions/retailers are using big data to transform themselves in to next generation enterprises? Do you want to be part of the world class next generation organisations to change the game rules of the strategy making and to zoom your career to newer heights? Here is the power of data science in the form of Data mining concepts which are considered most powerful techniques in big data analytics. Data Mining with R unveils underlying amazing patterns, wonderful insights which go unnoticed otherwise, from the large amounts of data. Data mining tools predict behaviours and future trends, allowing businesses to make proactive, unbiased and scientific-driven decisions. Data mining has powerful tools and techniques that answer business questions in a scientific manner, which traditional methods cannot answer. Adoption of data mining concepts in decision making changed the companies, the way they operate the business and improved revenues significantly. Companies in a wide range of industries such as Information Technology, Retail, Telecommunication, Oil and Gas, Finance, Health care are already using data mining tools and techniques to take advantage of historical data and to create their future business strategies. Data mining can be broadly categorized into two branches i.e. supervised learning and unsupervised learning. Unsupervised learning deals with identifying significant facts, relationships, hidden patterns, trends and anomalies. Clustering, Principle Component Analysis, Association Rules, etc., are considered unsupervised learning. Supervised learning deals with prediction and classification of the data with machine learning algorithms. Weka is most popular tool for supervised learning. Topics You Will Learn… Unsupervised learning: Introduction to datamining Dimension reduction techniques Principal Component Analysis (PCA) Singular Value Decomposition (SVD) Association rules / Market Basket Analysis / Affinity Filtering Recommender Systems / Recommendation Engine / Collaborative Filtering Network Analytics – Degree centrality, Closeness Centrality, Betweenness Centrality, etc. Cluster Analysis Hierarchical clustering K-means clustering Supervised learning: Overview of machine learning / supervised learning Data exploration methods Basic classification algorithms Decision trees classifier Random Forest K-Nearest Neighbours Bayesian classifiers: Naïve Bayes and other discriminant classifiers Perceptron and Logistic regression Neural networks Advanced classification algorithms Bayesian Networks Support Vector machines Model validation and interpretation Multi class classification problem Bagging (Random Forest) and Boosting (Gradient Boosted Decision Trees) Regression analysis Tools You Will Learn… R: R is a programming language to carry out complex statistical computations and data visualization. R is also open source software and backed by large community all over the world who are contributing to enhancing the capability. R has many advantages over other tools available in the market and it has been rated No.1 among the data scientist community. Mode of Trainings : E-Learning Online Training ClassRoom Training --------------------------------------------------------------------------- For More Info Contact :: Toll Free (IND) : 1800 212 2120 | +91 80080 09704 Malaysia: 60 11 3799 1378 USA: 001-608-218-3798 UK: 0044 203 514 6638 AUS: 006 128 520-3240 Email: [email protected] Web: www.excelr.com
FIFA with Python | Finding FIFA Best XI Using Python | Python Training | Edureka
 
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** Python Training: https://www.edureka.co/python ** Put your Best XI for FIFA World Cup 2018 in the comment Section. This Edureka video analyzes FIFA Dataset using python to find out World's Best XI for FIFA World Cup 2018. ( FIFA Python Blog: http://bit.ly/2lGyxoe ). This video helps you to find the below players for 4-3-3 lineup: 1. World's Best Goalkeeper 2. World's Best Defenders 3. World's Best Mid-fielders 4. World's Best Attackers FIFA Dataset: https://www.kaggle.com/artimous/complete-fifa-2017-player-dataset-global/data#FullData.csv Subscribe to our channel to get video updates. Hit the subscribe button above. Check out our Python Training Playlist: https://goo.gl/Na1p9G #FIFAPython #FIFAAnalysis #PythonOnlineTraining How it Works? 1. This is a 5 Week Instructor led Online Course,40 hours of assignment and 20 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will be working on a real time project for which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - - - - About the Course Edureka’s Course on Python helps you gain expertise in various machine learning algorithms such as regression, clustering, decision trees, random forest, Naïve Bayes and Q-Learning. Throughout the Python Certification Course, you’ll be solving real life case studies on Media, Healthcare, Social Media, Aviation, HR. During our Python Certification Training, our instructors will help you to: 1. Master the basic and advanced concepts of Python 2. Gain insight into the 'Roles' played by a Machine Learning Engineer 3. Automate data analysis using python 4. Gain expertise in machine learning using Python and build a Real Life Machine Learning application 5. Understand the supervised and unsupervised learning and concepts of Scikit-Learn 6. Explain Time Series and it’s related concepts 7. Perform Text Mining and Sentimental analysis 8. Gain expertise to handle business in future, living the present 9. Work on a Real Life Project on Big Data Analytics using Python and gain Hands on Project Experience - - - - - - - - - - - - - - - - - - - Why learn Python? Programmers love Python because of how fast and easy it is to use. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging your programs is a breeze in Python with its built in debugger. Using Python makes Programmers more productive and their programs ultimately better. Python continues to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations. Python runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license. Python has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that Python is the next "Big Thing" and a must for Professionals in the Data Analytics domain. For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free). Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 7053 edureka!
Predicting Stock Prices - Learn Python for Data Science #4
 
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In this video, we build an Apple Stock Prediction script in 40 lines of Python using the scikit-learn library and plot the graph using the matplotlib library. The challenge for this video is here: https://github.com/llSourcell/predicting_stock_prices Victor's winning recommender code: https://github.com/ciurana2016/recommender_system_py Kevin's runner-up code: https://github.com/Krewn/learner/blob/master/FieldPredictor.py#L62 I created a Slack channel for us, sign up here: https://wizards.herokuapp.com/ Stock prediction with Tensorflow: https://nicholastsmith.wordpress.com/2016/04/20/stock-market-prediction-using-multi-layer-perceptrons-with-tensorflow/ Another great stock prediction tutorial: http://eugenezhulenev.com/blog/2014/11/14/stock-price-prediction-with-big-data-and-machine-learning/ This guy made 500K doing ML stuff with stocks: http://jspauld.com/post/35126549635/how-i-made-500k-with-machine-learning-and-hft Please share this video, like, comment and subscribe! That's what keeps me going. and please support me on Patreon!: https://www.patreon.com/user?u=3191693 Check out this youtube channel for some more cool Python tutorials: https://www.youtube.com/watch?v=RZF17FfRIIo Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/ Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w Hit the Join button above to sign up to become a member of my channel for access to exclusive content!
Views: 587052 Siraj Raval
What are the greatest challenges mining companies face when implementing technology? – Amazon Web
 
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We caught up with Matt Tuohy, Amazon Web Services, Head, Worldwide Business Development, Mining & Resources at the 2018 International Mining and Resources Conference (IMARC). In this video, Matt discusses the appetite for mining companies to adopt technologies and shares some of the challenges they face when transforming their business. Matt also provides insights on how mining companies can uptake digital and get a fast ROI. IMARC returns to the Melbourne Convention & Exhibition Centre from 28 – 31 October 2019. For more information please visit http://imarcmelbourne.com/ About IMARC The International Mining and Resources Conference (IMARC) is where global mining leaders connect with technology, finance and the future. Now in its 6th year, it is Australia’s largest mining event bringing together over 6000 decision makers, mining leaders, policy makers, investors, commodity buyers, technical experts, innovators and educators from over 90 countries to hear from 350 thought leaders and meet 250 exhibitors over four days of learning, deal-making and unparalleled networking.
What future for Big Data mining?
 
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Policymakers are showing growing interest for real-time analysis of public opinion and Big Data. From finance to political campaigners, social media have become a primary source of information, especially when it comes to understanding public opinion trends. However, the potential of social media still needs to be fully exploited. With the explosion of structured and unstructured Big Data, the ability to harness information has become paramount for those who want to successfully use information originating from social media. On the regulatory side, the European Commission wants to promote the data-driven economy as part of its Digital Single Market strategy. The strategy includes better online access and digitalisation as a driver for growth.
Views: 966 SSIX Project
Data Mining using R | R Tutorial for Beginners | Data Mining Tutorial for Beginners 2018 | ExcelR
 
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ExcelR Data Mining Tutorial for Beginners 2018 - Introduction to Data mining using R language. Data Mining Certification Training Course Content : https://www.excelr.com/data-mining/ Introduction to Data Mining Tutorials : https://youtu.be/uNrg8ep_sEI What is Data Mining? Big data!!! Are you demotivated when your peers are discussing about data science and recent advances in big data. Did you ever think how Flip kart and Amazon are suggesting products for their customers? Do you know how financial institutions/retailers are using big data to transform themselves in to next generation enterprises? Do you want to be part of the world class next generation organisations to change the game rules of the strategy making and to zoom your career to newer heights? Here is the power of data science in the form of Data mining concepts which are considered most powerful techniques in big data analytics. Data Mining with R unveils underlying amazing patterns, wonderful insights which go unnoticed otherwise, from the large amounts of data. Data mining tools predict behaviours and future trends, allowing businesses to make proactive, unbiased and scientific-driven decisions. Data mining has powerful tools and techniques that answer business questions in a scientific manner, which traditional methods cannot answer. Adoption of data mining concepts in decision making changed the companies, the way they operate the business and improved revenues significantly. Companies in a wide range of industries such as Information Technology, Retail, Telecommunication, Oil and Gas, Finance, Health care are already using data mining tools and techniques to take advantage of historical data and to create their future business strategies. Data mining can be broadly categorized into two branches i.e. supervised learning and unsupervised learning. Unsupervised learning deals with identifying significant facts, relationships, hidden patterns, trends and anomalies. Clustering, Principle Component Analysis, Association Rules, etc., are considered unsupervised learning. Supervised learning deals with prediction and classification of the data with machine learning algorithms. Weka is most popular tool for supervised learning. Topics You Will Learn… Unsupervised learning: Introduction to datamining Dimension reduction techniques Principal Component Analysis (PCA) Singular Value Decomposition (SVD) Association rules / Market Basket Analysis / Affinity Filtering Recommender Systems / Recommendation Engine / Collaborative Filtering Network Analytics – Degree centrality, Closeness Centrality, Betweenness Centrality, etc. Cluster Analysis Hierarchical clustering K-means clustering Supervised learning: Overview of machine learning / supervised learning Data exploration methods Basic classification algorithms Decision trees classifier Random Forest K-Nearest Neighbours Bayesian classifiers: Naïve Bayes and other discriminant classifiers Perceptron and Logistic regression Neural networks Advanced classification algorithms Bayesian Networks Support Vector machines Model validation and interpretation Multi class classification problem Bagging (Random Forest) and Boosting (Gradient Boosted Decision Trees) Regression analysis Tools You Will Learn… R: R is a programming language to carry out complex statistical computations and data visualization. R is also open source software and backed by large community all over the world who are contributing to enhancing the capability. R has many advantages over other tools available in the market and it has been rated No.1 among the data scientist community. Mode of Trainings : E-Learning Online Training ClassRoom Training --------------------------------------------------------------------------- For More Info Contact :: Toll Free (IND) : 1800 212 2120 | +91 80080 09704 Malaysia: 60 11 3799 1378 USA: 001-608-218-3798 UK: 0044 203 514 6638 AUS: 006 128 520-3240 Email: [email protected] Web: www.excelr.com
4 Steps to Becoming an HR Analytics Champion
 
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Join us on Tuesday, January 29th 10AM PST / 1PM EST to learn more about the latest trends impacting data in HR and get actionable tips to help you and your team: · Understand what’s driving the rise of analytics in HR · Learn how early adopters are leveraging data & insights · Discover how to build a data-driven culture · See how you can apply analytics to answer your critical talent questions Get all of your questions answered during our live Q&A and walk away from this webcast with clear steps on how to create more data-driven talent strategies.
Data Science in 30 Minutes: Predicting Content Demand with Machine Learning
 
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Netflix is well-known for its data-driven recommendations that seek to customize the user experience for every subscriber. But data science at Netflix extends far beyond that - from optimizing streaming and content caching to informing decisions about the TV shows and films available on the service. The talk covered work done by Becky and the Content Data Science team at Netflix, which seeks to evaluate where Netflix should spend their next content dollar using machine learning and predictive models. The Data Incubator is a data science education company based in NYC, DC, and SF with both corporate training as well as recruiting services. For data science corporate training, we offer customized, in-house corporate training solutions in data and analytics. For data science hiring, we run a free 8 week fellowship training PhDs to become data scientists. The fellowship selects 2% of its 2000+ quarterly applicants and is free for Fellows. Hiring companies (including EBay, Capital One, Pfizer) pay a recruiting fee only if they successfully hire. You can read about us on Harvard Business Review, VentureBeat, or The Next Web, or read about our alumni at LinkedIn, Palantir or the NYTimes. http://thedataincubator.com About the speakers: Dr. Becky Tucker is a Senior Data Scientist at Netflix, a streaming media and entertainment company based in Los Gatos, CA. She holds a PhD in Physics from Caltech. At Netflix, Becky works on models that predict the demand for TV shows and movies. Michael Li founded The Data Incubator, a New York-based training program that turns talented PhDs from academia into workplace-ready data scientists and quants. The program is free to Fellows, employers engage with the Incubator as hiring partners. Previously, he worked as a data scientist (Foursquare), Wall Street quant (D.E. Shaw, J.P. Morgan), and a rocket scientist (NASA). He completed his PhD at Princeton as a Hertz fellow and read Part III Maths at Cambridge as a Marshall Scholar. At Foursquare, Michael discovered that his favorite part of the job was teaching and mentoring smart people about data science. He decided to build a startup to focus on what he really loves. Michael lives in New York, where he enjoys the Opera, rock climbing, and attending geeky data science events.
Views: 15667 The Data Incubator
TensorFlow Tutorial #23 Time-Series Prediction
 
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How to predict time-series data using a Recurrent Neural Network (GRU / LSTM) in TensorFlow and Keras. Demonstrated on weather-data. https://github.com/Hvass-Labs/TensorFlow-Tutorials
Views: 66548 Hvass Laboratories
10 Myths About Data Science | Uncovering Data Science Myths | Data Science Training | Edureka
 
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** Data Scientist Master Program: https://www.edureka.co/masters-program/data-scientist-certification ** This Edureka live session on “10 Data Science Myths" attempts to take down some of the misconceptions about Data Science and gives a much clearer picture of what data science really is. Check out our Data Science Tutorial blog series: http://bit.ly/data-science-blogs Check out our complete Youtube playlist here: http://bit.ly/data-science-playlist ------------------------------------- Do subscribe to our channel and hit the bell icon to never miss an update from us in the future: https://goo.gl/6ohpTV Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Slideshare: https://www.slideshare.net/EdurekaIN/ #edureka #edurekadatascience #datascientist #datasciencemyths #top10datasciencemyths -------------------------------------- How it Works? 1. This is a 30-hour Instructor-led Online Course. 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training, you will be working on a real-time project for which we will provide you a Grade and a Verifiable Certificate! ------------------------------------- About the Course Edureka's Data Science Training lets you gain expertise in Machine Learning Algorithms like K-Means Clustering, Decision Trees, Random Forest, and Naive Bayes using R. Data Science Training encompasses a conceptual understanding of Statistics, Time Series, Text Mining and an introduction to Deep Learning. Throughout this Data Science Course, you will implement real-life use-cases on Media, Healthcare, Social Media, Aviation and HR. ------------------------------------- Who should go for this course? The market for Data Analytics is growing across the world and this strong growth pattern translates into a great opportunity for all the IT Professionals. Our Data Science Training helps you to grab this opportunity and accelerate your career by applying the techniques on different types of Data. It is best suited for: Developers aspiring to be a 'Data Scientist' Analytics Managers who are leading a team of analysts Business Analysts who want to understand Machine Learning (ML) Techniques Information Architects who want to gain expertise in Predictive Analytics 'R' professionals who wish to work Big Data Analysts wanting to understand Data Science methodologies ------------------------------------- Why learn Data Science? Data science is an evolutionary step in interdisciplinary fields like the business analysis that incorporate computer science, modeling, statistics, and analytics. To take complete benefit of these opportunities, you need structured training with an updated curriculum as per current industry requirements and best practices. Besides strong theoretical understanding, you need to work on various real-life projects using different tools from multiple disciplines to gather a data set, process and derive insights from the data set, extract meaningful data from the set, and interpret it for decision-making purposes. Additionally, you need the advice of an expert who is currently working in the industry tackling real-life data-related challenges. ------------------------------------- Got a question on the topic? Please share it in the comment section below and our experts will answer it for you. For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free).
Views: 3324 edureka!
K Means Clustering Algorithm | K Means Example in Python | Machine Learning Algorithms | Edureka
 
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** Python Training for Data Science: https://www.edureka.co/python ** This Edureka Machine Learning tutorial (Machine Learning Tutorial with Python Blog: https://goo.gl/fe7ykh ) series presents another video on "K-Means Clustering Algorithm". Within the video you will learn the concepts of K-Means clustering and its implementation using python. Below are the topics covered in today's session: 1. What is Clustering? 2. Types of Clustering 3. What is K-Means Clustering? 4. How does a K-Means Algorithm works? 5. K-Means Clustering Using Python Machine Learning Tutorial Playlist: https://goo.gl/UxjTxm Subscribe to our channel to get video updates. Hit the subscribe button above. How it Works? 1. This is a 5 Week Instructor led Online Course,40 hours of assignment and 20 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will be working on a real time project for which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - - - - About the Course Edureka's Python Online Certification Training will make you an expert in Python programming. It will also help you learn Python the Big data way with integration of Machine learning, Pig, Hive and Web Scraping through beautiful soup. During our Python Certification training, our instructors will help you: 1. Programmatically download and analyze data 2. Learn techniques to deal with different types of data – ordinal, categorical, encoding 3. Learn data visualization 4. Using I python notebooks, master the art of presenting step by step data analysis 5. Gain insight into the 'Roles' played by a Machine Learning Engineer 6. Describe Machine Learning 7. Work with real-time data 8. Learn tools and techniques for predictive modeling 9. Discuss Machine Learning algorithms and their implementation 10. Validate Machine Learning algorithms 11. Explain Time Series and its related concepts 12. Perform Text Mining and Sentimental analysis 13. Gain expertise to handle business in future, living the present - - - - - - - - - - - - - - - - - - - Why learn Python? Programmers love Python because of how fast and easy it is to use. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging your programs is a breeze in Python with its built in debugger. Using Python makes Programmers more productive and their programs ultimately better. Python continues to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations. Python runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license. Python has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that Python is the next "Big Thing" and a must for Professionals in the Data Analytics domain. For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free). Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Customer Review Sairaam Varadarajan, Data Evangelist at Medtronic, Tempe, Arizona: "I took Big Data and Hadoop / Python course and I am planning to take Apache Mahout thus becoming the "customer of Edureka!". Instructors are knowledge... able and interactive in teaching. The sessions are well structured with a proper content in helping us to dive into Big Data / Python. Most of the online courses are free, edureka charges a minimal amount. Its acceptable for their hard-work in tailoring - All new advanced courses and its specific usage in industry. I am confident that, no other website which have tailored the courses like Edureka. It will help for an immediate take-off in Data Science and Hadoop working."
Views: 46780 edureka!
AI vs Machine Learning vs Deep Learning | Machine Learning Training with Python | Edureka
 
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** NIT Warangal Post Graduate Program on AI and Machine Learning: https://www.edureka.co/nitw-ai-ml-pgp ** This Edureka Machine Learning tutorial (Machine Learning Tutorial with Python Blog: https://goo.gl/fe7ykh ) on "AI vs Machine Learning vs Deep Learning" talks about the differences and relationship between AL, Machine Learning and Deep Learning. Below are the topics covered in this tutorial: 1. AI vs Machine Learning vs Deep Learning 2. What is Artificial Intelligence? 3. Example of Artificial Intelligence 4. What is Machine Learning? 5. Example of Machine Learning 6. What is Deep Learning? 7. Example of Deep Learning 8. Machine Learning vs Deep Learning Machine Learning Tutorial Playlist: https://goo.gl/UxjTxm - - - - - - - - - - - - - - - - - Subscribe to our channel to get video updates. Hit the subscribe button above: https://goo.gl/6ohpTV Instagram: https://www.instagram.com/edureka_learning Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Telegram: https://t.me/edurekaupdates - - - - - - - - - - - - - - - - - #edureka #AIvsMLvsDL #PythonTutorial #PythonMachineLearning #PythonTraining How it Works? 1. This is a 5 Week Instructor led Online Course,40 hours of assignment and 20 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will be working on a real time project for which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - - - - About the Course Edureka's Python Online Certification Training will make you an expert in Python programming. It will also help you learn Python the Big data way with integration of Machine learning, Pig, Hive and Web Scraping through beautiful soup. During our Python Certification training, our instructors will help you: 1. Master the Basic and Advanced Concepts of Python 2. Understand Python Scripts on UNIX/Windows, Python Editors and IDEs 3. Master the Concepts of Sequences and File operations 4. Learn how to use and create functions, sorting different elements, Lambda function, error handling techniques and Regular expressions ans using modules in Python 5. Gain expertise in machine learning using Python and build a Real Life Machine Learning application 6. Understand the supervised and unsupervised learning and concepts of Scikit-Learn 7. Master the concepts of MapReduce in Hadoop 8. Learn to write Complex MapReduce programs 9. Understand what is PIG and HIVE, Streaming feature in Hadoop, MapReduce job running with Python 10. Implementing a PIG UDF in Python, Writing a HIVE UDF in Python, Pydoop and/Or MRjob Basics 11. Master the concepts of Web scraping in Python 12. Work on a Real Life Project on Big Data Analytics using Python and gain Hands on Project Experience - - - - - - - - - - - - - - - - - - - Why learn Python? Programmers love Python because of how fast and easy it is to use. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging your programs is a breeze in Python with its built in debugger. Using Python makes Programmers more productive and their programs ultimately better. Python continues to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations. Python runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license. Python has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that Python is the next "Big Thing" and a must for Professionals in the Data Analytics domain. For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free). Customer Review Sairaam Varadarajan, Data Evangelist at Medtronic, Tempe, Arizona: "I took Big Data and Hadoop / Python course and I am planning to take Apache Mahout thus becoming the "customer of Edureka!". Instructors are knowledge... able and interactive in teaching. The sessions are well structured with a proper content in helping us to dive into Big Data / Python. Most of the online courses are free, edureka charges a minimal amount. Its acceptable for their hard-work in tailoring - All new advanced courses and its specific usage in industry. I am confident that, no other website which have tailored the courses like Edureka. It will help for an immediate take-off in Data Science and Hadoop working."
Views: 512277 edureka!
Why Machine Learning is The Future? | Sundar Pichai Talks About Machine Learning
 
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Why Machine Learning is The Future? | Sundar Pichai Talks About Machine Learning https://acadgild.com/big-data/deep-learning-course-training-certification?aff_id=6003&source=youtube&account=5cFUZ03Sbhc&campaign=youtube_channel&utm_source=youtube&utm_medium=sundarpichai&utm_campaign=youtube_channel It is 2017 and one technology which is expected to bring in a sea of innovation is Machine Learning. Be it the day to day life or high-end sophisticated innovation, the world is slowly but surely moving forward to become more Machine Learning reliant. Products of the Internet giant like Google or Facebook are heavily embedded around Machine Learning. "We are making a big bet on machine learning and artificial intelligence. Advancement in machine learning will make a big difference in many many fields.", the Google CEO, Sundar Pichai said at IIT Kharagpur pointing out how effectively computers recognize image, voice or speech. For more updates on courses and tips follow us on: Facebook: https://www.facebook.com/acadgild Twitter: https://twitter.com/acadgild LinkedIn: https://www.linkedin.com/company/acadgild
Views: 734060 ACADGILD
Stock Price Prediction | AI in Finance
 
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Can AI be used in the financial sector? Of course! In fact, finance was one of the pioneering industries that started using AI in the early 80s for market prediction. Since then, major financial firms and hedge funds have adopted AI technologies for everything from portfolio optimization, to credit lending, to stock betting. In this video, we'll go over all the different ways AI can be used in applied finance, then build a stock price prediction algorithm in python using Keras and Tensorflow. Code for this video: https://github.com/llSourcell/AI_in_Finance Please Subscribe! And like. And comment. That's what keeps me going. Want more education? Connect with me here: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology instagram: https://www.instagram.com/sirajraval More learning resources: https://hackernoon.com/unsupervised-machine-learning-for-fun-profit-with-basket-clusters-17a1161e7aa1 https://www.datacamp.com/community/tutorials/finance-python-trading http://www.cuelogic.com/blog/python-in-finance-analytics-artificial-intelligence/ https://www.udacity.com/course/machine-learning-for-trading--ud501 https://www.oreilly.com/learning/algorithmic-trading-in-less-than-100-lines-of-python-code Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ Sign up for the next course at The School of AI: https://www.theschool.ai And please support me on Patreon: https://www.patreon.com/user?u=3191693 Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w Hit the Join button above to sign up to become a member of my channel for access to exclusive content!
Views: 182406 Siraj Raval
15 Hot Trending PHD Research Topics in Data Mining 2018
 
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15 Hot Trending Data Mining Research Topics 2018 1. Medical Data Mining 2. Education Data Mining 3. Data Mining with Cloud Computing 4. Efficiency of Data Mining Algorithms 5. Signal Processing 6. Social Media Analytics 7. Data Mining in Medical Science 8. Government Domain 9. Financial Data Analysis 10. Financial Accounting Fraud Detection 11. Customer Analysis 12. Financial Growth Analysis using Data Mining 13. Data Mining and IOT 14. Data Mining for Counter-Terrorism Key Research Application Fields: • Crisp-DM • Oracle Data mining • Web Mining • Open NN • Data Warehousing • Text Mining WHY YOU NEED TO OUTSOURCE TO PhD Assistance: a) Unlimited revisions b) 24/7 Admin Support c) Plagiarism Generate d) Best Possible Turnaround time e) Access to High qualified technical coordinators and expertise f) Support: Skype, Live Chat, Phone, Email Contact us: India: +91 8754446690 UK: +44-1143520021 Email: [email protected] Visit Webpage: https://goo.gl/HwJgqQ Visit Website: http://www.phdassistance.com
Views: 5509 PhD Assistance
Free Digital Marketing Training Video | Introduction to Digital Marketing - Part 1
 
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https://acadgild.com/web-development/digital-marketing?utm_campaign=Enrol-1CYBkEJV7T4&utm_medium=VM&utm_source=youtube Free Digital Marketing Training Video | Online Digital Marketing Course - Part 1 Watch this free digital marketing online tutorial episodes to learn digital marketing, here you go with the first part of the course. Introduction to Digital marketing Here is a tentative introduction to Digital Marketing Certification Training. While talking about digital marketing, we essentially talk about building our business prominent on various digital channels. These channels include search, social, video, e-mail, and display. You see, nowadays customers are present online all the time and the way they are hooked up with the digital devices, it has become for brands, services, individuals and organisations to be present on the digital platforms. Internet is continuously changing the way customers shopped or searched anything. With the internet, they can find anything at a touch of a finger. This power that has been possessed by the customer has opened the plethora of opportunities for the marketers to promote their brands by reaching out to their target customer. Traditional media has taken a back seat with various media channels such as print media becoming obsolete with decreasing reader base. Digital Media has provided a way to measure everything. All of a sudden marketers have found a way to understand ROI on their marketing activities. As a business you must understand that there is 3 kinds of digital media available – Owned, Earned and paid. Your own platforms like your blog or a website are your owned properties. Your social mentions or anywhere you are talked about forms Earned Media. Paid media is the media that you have paid money for. This can be a paid article on a website or a paid review. Together these 3 forms a pivotal role in building your digital presence. In time with this course, you will understand the usage benefits and various methods to make the best out of every media type to build your business successfully on digital channels. What is Digital Marketing? “The science and art of exploring, creating, and delivering value to satisfy the needs of a target market at a profit. Marketing identifies unfulfilled needs and desires.” Digital marketing Definition “The marketing of products or services using digital channels to reach consumers. The key objective is to promote brands through various forms of digital media.” Digital Marketing Terminologies: Digital Marketing comprises of various domains and terminologies like • SEO or Organic Search • Social Media • Link Building • Call to Action • Data Mining • Global Reach • Google Analytics • PPC or Google AdWords etc. Digital Economy is growing – • More than 40% of world population now uses the Internet as per a 2014 survey • We spend 6.15 hours on an average per day on online devices • According to market research firm eMarketer, consumers worldwide spent appx. $1.672 trillion online in 2015 Digital Marketing is extremely useful for you as 68% companies have a separate digital marketing budget for their businesses. Companies are increasing their digital budgets to cater to their customers. Digital Marketing Trends 2016 Here are the 5 Digital Trends to watch out for in 2016– 1. Video Ads – With an average CTR of 1.8% video ads are spreading like wildfire. 2. Mobile Apps – People are using apps for everything they do today from commuting to communicating. Since google too is using mobile apps as ranking factor , the shift from websites to app has begun 3. Virtual Assistant – With technology like Siri and Okay Google, businesses need to create content that can easily be understood by these platforms 4. Wearable Technology – The use of Wearable is set to grow 35% every year. We need to find the best way communicating with our customers with the help of this technology 5. Ad Budget – Digital Marketing ad budgets are on rise. Thanks for watching the video, do subscribe the channel to be notified on the next lesson! For more updates on courses and tips follow us on: Facebook: https://www.facebook.com/acadgild Twitter: https://twitter.com/acadgild LinkedIn: https://www.linkedin.com/company/acadgild
Views: 29488 ACADGILD
Time Series Data Mining Forecasting with Weka
 
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I am sorry for my poor english. I hope it helps you. when i take the data mining course, i had searched it but i couldnt. So i decided to share this video with you.
Views: 25516 Web Educator
Digital Transformation: Future Scenarios 2030 | Deloitte
 
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Digital transformation will bring comprehensive changes for companies. How will Germany look like in 2030 and how competitive will german companies be in the future? Deloitte's experts have developed four future scenarios that take a holistic view of the many influencing factors and their complex interactions and highlight the opportunities and risks for german companies. Die Digitale Transformation wird für Unternehmen weitreichende und umfassende Veränderungen mit sich bringen. Wie wird der Standort Deutschland im Jahr 2030 aussehen und wie konkurrenzfähig werden deutsche Unternehmen in Zukunft sein? Die Experten von Deloitte haben vier Zukunftsszenarien entwickelt, die in einer ganzheitlichen Betrachtung die vielen Einflussfaktoren und ihre komplexen Wechselwirkungen einbeziehen und die Chancen und Risiken für deutsche Unternehmen aufzeigen. For more information please go to: http://deloi.tt/2rgN9Al Follow us on Social Media: ● LinkedIn: https://www.linkedin.com/company/deloitte-deutschland ● Twitter: https://twitter.com/DeloitteDE ● Facebook: https://www.facebook.com/Deloitte.Deutschland/ ● XING: https://www.xing.com/company/deloitte ● Instagram: https://www.instagram.com/deloittedeutschlandkarriere/ ● Google+: https://plus.google.com/+DeloitteDeutschland Get more information about Deloitte on our website: ● Website: https://www2.deloitte.com/de/ ● Karriere: https://www.deloitte.com/de/karriere
Views: 78371 Deloitte Deutschland
APPLICATION OF BIG DATA IN EDUCATION DATA MINING
 
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APPLICATION OF BIG DATA IN EDUCATION DATA MINING
Views: 315 Chennai Sunday
Mining electronic health records and the web for drug repurposing,  Kira Radinsky (eBay | Technion)
 
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Check out all the Strata Data Conference keynotes, sessions, and tutorials here: https://www.safaribooksonline.com/library/view/strata-data-conference/9781491985373/ Researchers decide on exploratory targets for drug repurposing—the process of applying known drugs in new ways to treat diseases—based on trends in research and observations on small numbers of cases, leading to potentially costly biases of focus and neglect. Kira Radinsky offers an overview of a system that jointly mines 10 years of nationwide medical records of more than 1.5 million people and extracts medical knowledge from Wikipedia to help reduce spurious correlations and provide guidance about drug repurposing. The resulting system seeks to identify potential biological processes to justify potential influences between medications and target diseases via links on a graph constructed from Wikipedia data. Kira shares results of the system on two studies on drug repurposing for hypertension and diabetes. In both cases, the algorithm identified drug families that were previously unknown, and clinical opinion by experts in the field and clinical trials on those drug families suggest that these drugs show promise. Subscribe to O'Reilly on YouTube: http://goo.gl/n3QSYi Follow O'Reilly on: Twitter: http://twitter.com/oreillymedia Facebook: http://facebook.com/OReilly Instagram: https://www.instagram.com/oreillymedia LinkedIn: https://www.linkedin.com/company-beta/8459/
Views: 3861 O'Reilly
The Future of Testing: Trends, Tactics & Predictions
 
01:03:53
Rapid advancement in digital technologies have accelerated the need to deliver more value to customers, faster. This ever-increasing demand for both speed and quality has put software testing and delivery under tremendous stress. How can you advance your development and testing capabilities to meet digital market demand, today and in the future? Is it only about technology and automation? What about testers—will new practices such as AI save us? Join this web seminar for a discussion with Forrester Research’s Diego Lo Giudice and Perfecto’s Tzvika Shahaf about the future state of testing. Learn what’s next for test and dev teams and the people who drive them. We’ll talk about: -Where the development and testing market is headed and how you compare -Test automation challenges and how to overcome them -What’s next in test automation tools and technologies -Testing and development predictions for 2019
Views: 237 Perfecto
Free Cryptocurrency Course: Learn Everything You Need to Know About Cryptocurrencies Today!
 
06:03:57
Want more? Enroll in the full course at: https://www.udemy.com/the-complete-cryptocurrency-course-more-than-5-courses-in-1/?couponCode=WB73018CCC Here are more details on the full 24 hour version of this Comprehensive COMPLETE Cryptocurrency Course! I guarantee that this is THE most thorough cryptocurrency course available ANYWHERE on the market - or your money back (30 day money back guarantee). This course and the many exercises in this course are for beginner or advanced users in any country! By an Award Winning MBA professor who is a top selling online business teacher, top selling author, former Goldman Sachs employee, Columbia MBA (finance major) and venture capitalist who has invested in and sat on the boards of cryptocurrency companies since 2013 and a hedge fund industry veteran and founder. He is also the author of the #1 best selling business course on Udemy. THIS COMPLETE CRYPTOCURRENCY COURSE is 5+ courses in 1! Cryptocurrency Investing Cryptocurrency Mining Cryptocurrency Wallets Cryptocurrency Exchanges Blockchain Creating a Diversified Portfolio & Much More! Also included in this course is a very comprehensive Excel spreadsheet that contains more than 30 Cryptocurrency exercises to help you learn everything you need to know about cryptocurrencies (whether you are a beginner or an advanced user). No prior cryptocurrency or finance or accounting or tech or Excel experience is required to take this course. We Will Cover More than 10 Cryptocurrencies in this Course (and how to buy & sell each one, what are the pros and cons of each one & how to mine each one): Bitcoin Ethereum Ripple Litecoin Monero Zcash Dash NEO Cardano Stellar ...and more (this course will constantly be updated with more cryptocurrencies) We Will Cover More than 5 Wallets in this Course (how to set one up, the pros & cons of all 5 wallet types and how to transfer money between them): QR Code Wallets Four USB Wallets (Trezor. Ledger Nano S, DigitalBitBox & KeepKey) Coinbase Electrum Blockchain ...and more (this course will constantly be updated with more wallets) We Will Cover the More than 5 Exchanges in this Course (how to transact with each one): GDAX Poloniex Kraken Bittrex Gemini Binance ...& more (this course will constantly be updated with more exchanges) Here Are Some More Topics That We Will Cover In This Course: The Future of Money & What is Blockchain? Introduction to 10+ Cryptocurrencies (Mining, Investing & Much More) Create an Investment Portfolio of Cryptocurrencies Understand What Makes a Great Cryptocurrency as A Great Long-Term Investment Introduction to 5+ Wallets to Use to Store Your Cryptocurrencies Introduction to 5+ Exchanges to Use to Buy or Sell Cryptocurrencies Introduction to Mining & Building a Mining PC from Scratch! Cryptocurrency Investment Framework (made in Excel) Watching out for Scams & Managing Risk What Are the Biggest Mistakes New Investors Make in Cryptocurrencies? How to Identify the Next Great Cryptocurrency (What to Look For & Watch Out For) When Should You Buy or Sell a Cryptocurrency? How Do You Read Charts & Look for Buy or Sell Signals What Makes a Great Wallet (What to Look For From Researching a Wallet) Introduction to ICOs + What Makes a Great ICO (What To Look For From Researching An ICO More than 100 Great Online Cryptocurrency Resources You can use the comprehensive Excel exercise document in this course on a Mac or on a PC (I recommend having Excel version 2013 or later in order to complete all of the cryptocurrency exercises in this course). This course and the included comprehensive Complete Cryptocurrency Excel dashboard exercise file is a roadmap for your personal & technical/finance cryptocurrency success. All of the tools you need to be successful with cryptocurrencies are included in this course & the entire course is based on real life Practical Knowledge and experience & not based on theory. Please click the take this course button so you can take your cryptocurrency skills to the next level. Requirements: No prior technology or cryptocurrency or finance or accounting or Excel experience is required to take this course. Please note that Excel 2013 (or a newer version) is recommended in order to complete some of the exercises in this course. The Excel exercises in this course work on the Windows and Mac versions of Excel. Who is the target audience? Anyone in ANY country interested in learning EVERYTHING about cryptocurrency can take this course as this 23+ hour COMPLETE course is 5+ courses in 1 (1: Investing, 2: Mining, 3: Wallets, 4: Blockchain , 5: Transacting, 6: Creating a Diversified Portfolio & Much More!) *** Again, I guarantee that this is THE most thorough cryptocurrency course available ANYWHERE on the market - or your money back (30 day money back guarantee). *** Enroll in the full course at: https://www.udemy.com/the-complete-cryptocurrency-course-more-than-5-courses-in-1/?couponCode=WB73018CCC Thanks, Chris Haroun
How Publishers Can Take Advantage of Machine Learning (Cloud Next '18)
 
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Hearst Newspapers uses Google Cloud Machine Learning infrastructure to automate and create value in the newspaper business. A recent case study has been published detailing this. Also Hearst Newspapers is using TensorFlow to build state-of-the-art recommendation systems. MLAI200 Event schedule → http://g.co/next18 Watch more Machine Learning & AI sessions here → http://bit.ly/2zGKfcg Next ‘18 All Sessions playlist → http://bit.ly/Allsessions Subscribe to the Google Cloud channel! → http://bit.ly/NextSub
Complete Data Science Course | What is Data Science? | Data Science for Beginners | Edureka
 
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** Data Science Master Program: https://www.edureka.co/masters-program/data-scientist-certification ** This Edureka video on "Data Science" provides an end to end, detailed and comprehensive knowledge on Data Science. This Data Science video will start with basics of Statistics and Probability and then move to Machine Learning and Finally end the journey with Deep Learning and AI. For Data-sets and Codes discussed in this video, drop a comment. This video will be covering the following topics: 1:23 Evolution of Data 2:14 What is Data Science? 3:02 Data Science Careers 3:36 Who is a Data Analyst 4:20 Who is a Data Scientist 5:14 Who is a Machine Learning Engineer 5:44 Salary Trends 6:37 Road Map 9:06 Data Analyst Skills 10:41 Data Scientist Skills 11:47 ML Engineer Skills 12:53 Data Science Peripherals 13:17 What is Data ? 15:23 Variables & Research 17:28 Population & Sampling 20:18 Measures of Center 20:29 Measures of Spread 21:28 Skewness 21:52 Confusion Matrix 22:56 Probability 25:12 What is Machine Learning? 25:45 Features of Machine Learning 26:22 How Machine Learning works? 27:11 Applications of Machine Learning 34:57 Machine Learning Market Trends 36:05 Machine Learning Life Cycle 39:01 Important Python Libraries 40:56 Types of Machine Learning 41:07 Supervised Learning 42:27 Unsupervised Learning 43:27 Reinforcement Learning 46:27 Supervised Learning Algorithms 48:01 Linear Regression 58:12 What is Logistic Regression? 1:01:22 What is Decision Tree? 1:11:10 What is Random Forest? 1:18:48 What is Naïve Bayes? 1:30:51 Unsupervised Learning Algorithms 1:31:55 What is Clustering? 1:34:02 Types of Clustering 1:35:00 What is K-Means Clustering? 1:47:31 Market Basket Analysis 1:48:35 Association Rule Mining 1:51:22 Apriori Algorithm 2:00:46 Reinforcement Learning Algorithms 2:03:22 Reward Maximization 2:06:35 Markov Decision Process 2:08:50 Q-Learning 2:18:19 Relationship Between AI and ML and DL 2:20:10 Limitations of Machine Learning 2:21:19 What is Deep Learning ? 2:22:04 Applications of Deep Learning 2:23:35 How Neuron Works? 2:24:17 Perceptron 2:25:12 Waits and Bias 2:25:36 Activation Functions 2:29:56 Perceptron Example 2:31:48 What is TensorFlow? 2:37:05 Perceptron Problems 2:38:15 Deep Neural Network 2:39:35 Training Network Weights 2:41:04 MNIST Data set 2:41:19 Creating a Neural Network 2:50:30 Data Science Course Masters Program Subscribe to our channel to get video updates. Hit the subscribe button above. Check our complete Data Science playlist here: https://goo.gl/60NJJS Machine Learning Podcast: https://castbox.fm/channel/id1832236 Instagram: https://www.instagram.com/edureka_learning Slideshare: https://www.slideshare.net/EdurekaIN/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka #edureka #DataScienceEdureka #whatisdatascience #Datasciencetutorial #Datasciencecourse #datascience - - - - - - - - - - - - - - About the Master's Program This program follows a set structure with 6 core courses and 8 electives spread across 26 weeks. It makes you an expert in key technologies related to Data Science. At the end of each core course, you will be working on a real-time project to gain hands on expertise. By the end of the program you will be ready for seasoned Data Science job roles. - - - - - - - - - - - - - - Topics Covered in the curriculum: Topics covered but not limited to will be : Machine Learning, K-Means Clustering, Decision Trees, Data Mining, Python Libraries, Statistics, Scala, Spark Streaming, RDDs, MLlib, Spark SQL, Random Forest, Naïve Bayes, Time Series, Text Mining, Web Scraping, PySpark, Python Scripting, Neural Networks, Keras, TFlearn, SoftMax, Autoencoder, Restricted Boltzmann Machine, LOD Expressions, Tableau Desktop, Tableau Public, Data Visualization, Integration with R, Probability, Bayesian Inference, Regression Modelling etc. - - - - - - - - - - - - - - For more information, Please write back to us at [email protected] or call us at: IND: 9606058406 / US: 18338555775 (toll free)
Views: 48421 edureka!
Drones are now flying deep underground to map mines
 
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These drones are boldly going where no drone has gone before – deep underground. More companies are looking at ways to use drones underground or inside infrastructure for help with mapping, surveying, and search and rescue. ----- Want more? Find us online here: Web: https://www.createdigital.org.au/ Facebook: https://www.facebook.com/EngineersAustralia/ Twitter: https://twitter.com/create_digital_ Instagram: https://www.instagram.com/create.digital/ ----- Who we are: create tells the stories behind the people, trends and innovations shaping the engineering profession now and into the future.
Views: 1043 Create Digital
SFI Centre for Research Training in Machine Learning
 
00:55
http://www.sfi.ie/funding/centres-research-training/
What Are Python Modules? | Modules In Python | Python Tutorial For Beginners | Edureka
 
22:26
** Python Certification Training: https://www.edureka.co/python ** This Edureka Live video on 'Python Modules' will help you understand the concept of modules in python, why and how we can use modules in python. Below are the topics covered in this video: What Is A Python Module? How To Create A Python Module? How To Call A Python Module? Built-in Modules In Python Demo Python Tutorial Playlist: https://goo.gl/WsBpKe Blog Series: http://bit.ly/2sqmP4s #Edureka #EdurekaPython #ModulesinPython #pythonprojects #pythonprogramming #pythontutorial #PythonTraining #PythonEdureka #PythonModules Do subscribe to our channel and hit the bell icon to never miss an update from us in the future: https://goo.gl/6ohpTV Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Slideshare: https://www.slideshare.net/EdurekaIN ----------------------------------------------------------------------------------------------------------------------------------- How it Works? 1. This is a 5 Week Instructor-led Online Course,40 hours of assignment and 20 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training, you will be working on a real-time project for which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - - - - About the Course Edureka's Python Online Certification Training will make you an expert in Python programming. It will also help you learn Python the Big data way with integration of Machine learning, Pig, Hive and Web Scraping through beautiful soup. During our Python Certification training, our instructors will help you: 1. Master the Basic and Advanced Concepts of Python 2. Understand Python Scripts on UNIX/Windows, Python Editors and IDEs 3. Master the Concepts of Sequences and File operations 4. Learn how to use and create functions, sorting different elements, Lambda function, error handling techniques and Regular expressions ans using modules in Python 5. Gain expertise in machine learning using Python and build a Real Life Machine Learning application 6. Understand the supervised and unsupervised learning and concepts of Scikit-Learn 7. Master the concepts of MapReduce in Hadoop 8. Learn to write Complex MapReduce programs 9. Understand what is PIG and HIVE, Streaming feature in Hadoop, MapReduce job running with Python 10. Implementing a PIG UDF in Python, Writing a HIVE UDF in Python, Pydoop and/Or MRjob Basics 11. Master the concepts of Web scraping in Python 12. Work on a Real Life Project on Big Data Analytics using Python and gain Hands on Project Experience - - - - - - - - - - - - - - - - - - - Why learn Python? Programmers love Python because of how fast and easy it is to use. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging your programs is a breeze in Python with its built in debugger. Using Python makes Programmers more productive and their programs ultimately better. Python continues to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations. Python runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license. Python has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that Python is the next "Big Thing" and a must for Professionals in the Data Analytics domain. Who should go for python? Edureka’s Data Science certification course in Python is a good fit for the below professionals: · Programmers, Developers, Technical Leads, Architects · Developers aspiring to be a ‘Machine Learning Engineer' · Analytics Managers who are leading a team of analysts · Business Analysts who want to understand Machine Learning (ML) Techniques · Information Architects who want to gain expertise in Predictive Analytics · 'Python' professionals who want to design automatic predictive models For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free)
Views: 3114 edureka!
Python for Data Science | Python Data Science Tutorial | Data Science Certification | Edureka
 
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( Python Data Science Training : https://www.edureka.co/python ) This Edureka video on "Python For Data Science" explains the fundamental concepts of data science using python. It will also help you to analyze, manipulate and implement machine learning using various python libraries such as NumPy, Pandas and Scikit-learn. This video helps you to learn the below topics: 1. Need of Data Science 2. What is Data Science? 3. How Python is used for Data Science? 4. Data Manipulation in Python 5. Implement Machine Learning using Python 6. Demo Subscribe to our channel to get video updates. Hit the subscribe button above. Check out our Python Training Playlist: https://goo.gl/Na1p9G #Python #PythonForDataScience #PythonTutorial #PythonForBeginners #PythonOnlineTraining How it Works? 1. This is a 5 Week Instructor led Online Course,40 hours of assignment and 20 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will be working on a real time project for which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - - - - About the Course Edureka’s Data Science Course on Python helps you gain expertise in various machine learning algorithms such as regression, clustering, decision trees, random forest, Naïve Bayes and Q-Learning. Throughout the Data Science Certification Course, you’ll be solving real life case studies on Media, Healthcare, Social Media, Aviation, HR. During our Python Certification Training, our instructors will help you to: 1. Master the basic and advanced concepts of Python 2. Gain insight into the 'Roles' played by a Machine Learning Engineer 3. Automate data analysis using python 4. Gain expertise in machine learning using Python and build a Real Life Machine Learning application 5. Understand the supervised and unsupervised learning and concepts of Scikit-Learn 6. Explain Time Series and it’s related concepts 7. Perform Text Mining and Sentimental analysis 8. Gain expertise to handle business in future, living the present 9. Work on a Real Life Project on Big Data Analytics using Python and gain Hands on Project Experience - - - - - - - - - - - - - - - - - - - Why learn Python? Programmers love Python because of how fast and easy it is to use. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging your programs is a breeze in Python with its built in debugger. Using Python makes Programmers more productive and their programs ultimately better. Python continues to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations. Python runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license. Python has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that Python is the next "Big Thing" and a must for Professionals in the Data Analytics domain. For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free). Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 41747 edureka!
Humans Need Not Apply
 
15:01
Support Grey making videos: https://www.patreon.com/cgpgrey ## Robots, Etc: Terex Port automation: http://www.terex.com/port-solutions/en/products/new-equipment/automated-guided-vehicles/lift-agv/index.htm Command | Cat MieStar System.: http://www.catminestarsystem.com/capability_sets/command Bosch Automotive Technology: http://www.bosch-automotivetechnology.com/en/de/specials/specials_for_more_driving_safety/automated_driving/automated_driving.html Atlas Update: https://www.youtube.com/watch?v=SD6Okylclb8&list=UU7vVhkEfw4nOGp8TyDk7RcQ Kiva Systems: http://www.kivasystems.com PhantomX running Phoenix code: https://www.youtube.com/watch?v=rAeQn5QnyXo iRobot, Do You: https://www.youtube.com/watch?v=da-5Uw8GBks&list=UUB6E-44uKOyRW9hX378XEyg New pharmacy robot at QEHB: https://www.youtube.com/watch?v=_Ql1ZHSkUPk Briggo Coffee Experience: http://vimeo.com/77993254 John Deere Autosteer ITEC Pro 2010. In use while cultivating: https://www.youtube.com/watch?v=VAPfImWdkDw&t=19s The Duel: Timo Boll vs. KUKA Robot: https://www.youtube.com/watch?v=tIIJME8-au8 Baxter with the Power of Intera 3: https://www.youtube.com/watch?v=DKR_pje7X2A&list=UUpSQ-euTEYaq5VtmEWukyiQ Baxter Research Robot SDK 1.0: https://www.youtube.com/watch?v=wgQLzin4I9M&list=UUpSQ-euTEYaq5VtmEWukyiQ&index=11 Baxter the Bartender: https://www.youtube.com/watch?v=AeTs9tLsUmc&list=UUpSQ-euTEYaq5VtmEWukyiQ Online Cash Registers Touch-Screen EPOS System Demonstration: https://www.youtube.com/watch?v=3yA22B0rC4o Self-Service Check in: https://www.youtube.com/watch?v=OafuIBDzxxU Robot to play Flappy Bird: https://www.youtube.com/watch?v=kHkMaWZFePI e-david from University of Konstanz, Germany: https://vimeo.com/68859229 Sedasys: http://www.sedasys.com/ Empty Car Convoy: http://www.youtube.com/watch?v=EPTIXldrq3Q Clever robots for crops: http://www.crops-robots.eu/index.php?option=com_content&view=article&id=62&Itemid=61 Autonomously folding a pile of 5 previously-unseen towels: https://www.youtube.com/watch?v=gy5g33S0Gzo#t=94 LS3 Follow Tight: https://www.youtube.com/watch?v=hNUeSUXOc-w Robotic Handling material: https://www.youtube.com/watch?v=pT3XoqJ7lIY Caterpillar automation project: http://www.catminestarsystem.com/articles/autonomous-haulage-improves-mine-site-safety Universal Robots has reinvented industrial robotics: https://www.youtube.com/watch?v=UQj-1yZFEZI Introducing WildCat: https://www.youtube.com/watch?v=wE3fmFTtP9g The Human Brain Project - Video Overview: https://www.youtube.com/watch?v=JqMpGrM5ECo This Robot Is Changing How We Cure Diseases: https://www.youtube.com/watch?v=ra0e97Wiqds Jeopardy! - Watson Game 2: https://www.youtube.com/watch?v=kDA-7O1q4oo What Will You Do With Watson?: https://www.youtube.com/watch?v=Y_cqBP08yuA ## Other Credits Mandelbrot set: https://www.youtube.com/watch?v=NGMRB4O922I&list=UUoxcjq-8xIDTYp3uz647V5A Moore's law graph: http://en.wikipedia.org/wiki/File:PPTMooresLawai.jpg Apple II 1977: https://www.youtube.com/watch?v=CxJwy8NsXFs Beer Robot Fail m2803: https://www.youtube.com/watch?v=N4Lb_3_NMjE All Wales Ambulance Promotional Video: https://www.youtube.com/watch?v=658aiRoVp6s Clyde Robinson: https://www.flickr.com/photos/crobj/4312159033/in/photostream/ Time lapse Painting - Monster Spa: https://www.youtube.com/watch?v=ED14i8qLxr4
Views: 11260712 CGP Grey
Data Science Expert Webinar with R & Python | Data Science Training | Intellipaat
 
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This is a recording of Data Science webinar which covered the concept of Data Science, Which one to choose R or Python for Data Science, how to write code for Data Science & Career and Job Trends in Data Science. If you’ve enjoyed this video, Like us and Subscribe to our channel for more similar informative videos and free tutorials. Got any questions about Data Science? Ask us in the comment section below. Are you looking for something more? Enroll in our Data Science training course and become a certified Data Scientist (https://goo.gl/rTBCd7). It is a 35 hrs instructor led training provided by Intellipaat which is completely aligned with industry standards and certification bodies ------------------------------ Intellipaat Edge 1. 24x7 Life time Access & Support 2. Flexible Class Schedule 3. Job Assistance 4. Mentors with +14 yrs industry experience 5. Industry Oriented Courseware 6. Life time free Course Upgrade ------------------------------ Why take this course? There is a genuine deficiency of Data Scientists and this is a noteworthy worry for Top MNCs around the globe. This implies the significant enterprises are prepared to pay as much as possible pay rates for experts with the correct Data Science aptitudes. This Training Course prepares will all the most recent innovations in Big Data, examination, and R programming. Along these lines you can without much of a stretch take your vocation to the following level after fulfillment of this Course. ------------------------------ What you will learn in this course? This course will be covering following topics: 1. Prologue to Data Science in true, Project Life cycle, and Data Acquisition 2. Comprehend Machine Learning Algorithms 3. Concentrate the apparatuses and strategies of Experimentation, Evaluation and Project Deployment 4. Take in the idea of Prediction and Analysis Segmentation through Clustering 5. Incorporate R with Hadoop 6. Get prepared about the parts and obligations of a Data Scientist 7. Investigate ventures to introduce IMPALA 8. Live Projects on Data science, examination and Recommender Systems 9. Work on information mining, information structures, information control. ------------------------------ For more information: Please write us to [email protected] or call us at: +91-7847955955 Website: https://goo.gl/rTBCd7 Facebook: https://www.facebook.com/intellipaatonline LinkedIn: https://www.linkedin.com/in/intellipaat/ Twitter: https://www.twitter.com/intellipaat
Views: 445 Intellipaat
Uber’s Distributed Deep Learning on Apache Mesos w/ GPUs and Gang Scheduling (Speakers from Uber)
 
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For Uber, distributed deep learning is an essential part of the work on self-driving vehicles, trip forecasting, and fraud detection. With deep learning, Uber can speed up complex model training, scale out to hundreds of GPUs, and shard models that can not be fit into a single machine. With recent advances in deep learning models in self-driving car areas such as lane-detection, perception and so on, it is important to enable distributed deep learning with large-scale GPU clusters. Uber relies on Mesos’ key features such as GPU isolation, nested containers, high scalability and reliability; but they also developed their own system, Peloton, to add task preemption and placement, as well as a job/task lifecycle manager on top of Mesos’ resource allocation and task execution. This presentation, given at MesosCon 2017 in Los Angeles, features Min Cai, Anne Holler, Paul Mikesell, and Alex Sergeev, engineers at UBER, discussing the design and implementation of running distributed TensorFlow on top of Mesos clusters with hundreds of GPUs. Presenters discuss the architecture of their Peloton solution, and how Uber implements several features in its scheduler to support GPU and Gang scheduling, task discovery and dynamic port allocation. Finally, speakers show the speed up of distributed training on Mesos using Horovod, a framework for TensorFlow for image classification. About the speakers: Min Cai is a Staff Engineer at UBER working on cluster management. He received his Ph.D. degree in Computer Science from USC. Before joining Uber, he was a Sr. Staff Engineer at VMware working on vMotion and vSphere. Anne Holler is a software engineer at UBER. Paul Mikesell is director of infrastructure engineering and staff engineer at UBER. Alex Sergeev is a Senior Engineer at UBER working on scalable Deep Learning. He received his M.S. degree in Computer Science from MEPhI. Before joining UBER, he was Senior Engineer at Microsoft working on Big Data Mining.
Views: 1326 Mesosphere
Leveraging Technology to Overcome Today's Top Challenges in Mining
 
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Watch the full webinar here: http://bit.ly/1GZJfxb Deloitte’s recent report on the Top 10 Trends in Mining highlighted some of the biggest pains faced by mining companies today. From substantial costs of doing business, to labour pains, to a web of incomprehensible legislative hurdles it’s getting harder and harder for mining companies to keep their ducks in a row and optimize business performance. To add some clarity and guidance to the climate around mining, Intelex is proud to present "Leveraging Technology to Overcome Today’s Top Challenges in Mining", a free 30-minute webinar. Hosted by Intelex Mining Solutions Specialist Eric Tchao, this presentation looks at some of the key challenges that mining companies face today, and how they can save money, time and resources by leveraging streamlined technological tools. Key topics covered include: - Rising prices of energy, resources and commodities and the resultant impacts on mining operations around the world. - How to handle labour shortages, turnover, and the need for skilled mining professionals in the current economic climate. - Navigating the complex web of existing and emerging mining legislation and regulations among global markets. - Leveraging technology tools to build new efficiencies and overcome nascent burdens on the mining industry, and more. Try Intelex Free Today: http://bit.ly/1d24Ln1
Views: 82 intelexsoftware
Python Machine Learning Tutorial | Machine Learning Algorithms | Python Training | Edureka
 
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( Python Training : https://www.edureka.co/python ) This Edureka Python tutorial (Python Tutorial Blog: https://goo.gl/wd28Zr) gives an introduction to Machine Learning and how to implement machine learning algorithms in Python. Below are the topics covered in this tutorial: 1. Why Machine Learning? 2. What is Machine Learning? 3. Types of Machine Learning 4. Supervised Learning 5. KNN algorithm 6. Unsupervised Learning 7. K-means Clustering Algorithm Check out our playlist for more videos: https://goo.gl/Na1p9G Subscribe to our channel to get video updates. Hit the subscribe button above. #Python #PythonTutorial #PythonMachineLearning #PythonTraining How it Works? 1. This is a 5 Week Instructor led Online Course,40 hours of assignment and 20 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will be working on a real time project for which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - - - - About the Course Edureka's Python Online Certification Training will make you an expert in Python programming. It will also help you learn Python the Big data way with integration of Machine learning, Pig, Hive and Web Scraping through beautiful soup. During our Python Certification training, our instructors will help you: 1. Master the Basic and Advanced Concepts of Python 2. Understand Python Scripts on UNIX/Windows, Python Editors and IDEs 3. Master the Concepts of Sequences and File operations 4. Learn how to use and create functions, sorting different elements, Lambda function, error handling techniques and Regular expressions ans using modules in Python 5. Gain expertise in machine learning using Python and build a Real Life Machine Learning application 6. Understand the supervised and unsupervised learning and concepts of Scikit-Learn 7. Master the concepts of MapReduce in Hadoop 8. Learn to write Complex MapReduce programs 9. Understand what is PIG and HIVE, Streaming feature in Hadoop, MapReduce job running with Python 10. Implementing a PIG UDF in Python, Writing a HIVE UDF in Python, Pydoop and/Or MRjob Basics 11. Master the concepts of Web scraping in Python 12. Work on a Real Life Project on Big Data Analytics using Python and gain Hands on Project Experience - - - - - - - - - - - - - - - - - - - Why learn Python? Programmers love Python because of how fast and easy it is to use. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging your programs is a breeze in Python with its built in debugger. Using Python makes Programmers more productive and their programs ultimately better. Python continues to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations. Python runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license. Python has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that Python is the next "Big Thing" and a must for Professionals in the Data Analytics domain. For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free). Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Customer Review Sairaam Varadarajan, Data Evangelist at Medtronic, Tempe, Arizona: "I took Big Data and Hadoop / Python course and I am planning to take Apache Mahout thus becoming the "customer of Edureka!". Instructors are knowledge... able and interactive in teaching. The sessions are well structured with a proper content in helping us to dive into Big Data / Python. Most of the online courses are free, edureka charges a minimal amount. Its acceptable for their hard-work in tailoring - All new advanced courses and its specific usage in industry. I am confident that, no other website which have tailored the courses like Edureka. It will help for an immediate take-off in Data Science and Hadoop working."
Views: 154935 edureka!
Daniel Ameduri | Investment & Entrepreneurial Opportunities in the New Economy
 
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This Mining Stock Education episode features an interview with Daniel Ameduri, who is the president of Future Money Trends. Daniel became a self-made millionaire by seeking out and profiting from new trends and opportunities, both as an entrepreneur and as an investor. He shares his research and current opportunities in his popular Future Money Trends email newsletter. The Future Money Trends e-letter frequently focuses on the junior resource sector and often highlights specific junior mining companies. Daniel is also one of the earliest pioneers who developed financing and investing content on YouTube and one the most prolific Rick Rule interviewers on the web. His website is FutureMoneyTrends.com. 0:05 Introduction of topic and guest 1:44 Rising and dying trends in today’s economy and entrepreneurial opportunities available 3:51 Opportunities for developing second streams of income 8:40 Daniel shares his perspective on the current real estate market in the USA 11:24 Training our children in entrepreneurship, economics, and investing 18:33 Key macro-trends investors can profit from today 21:09 How Daniel proportions his investment capital between stocks, real estate, cash, and gold 23:20 Should a person who has substantial debt and a moderate income invest in speculative mining stocks? 26:01 Daniel shares regarding the mining sector and common pitfalls in this sector 29:21 Information on FutureMoneyTrends.com Sign up for our free newsletter and receive interview transcripts, stock profiles and investment ideas: http://eepurl.com/cHxJ39 The content found on MiningStockEducation.com is for informational purposes only and is not to be considered personal legal or investment advice or a recommendation to buy or sell securities or any other product. It is based on opinions, SEC filings, current events, press releases and interviews but is not infallible. It may contain errors and MiningStockEducation.com offers no inferred or explicit warranty as to the accuracy of the information presented. If personal advice is needed, consult a qualified legal, tax or investment professional. Do not base any investment decision on the information contained on MiningStockEducation.com or our videos. We may hold equity positions in some of the companies featured on this site and therefore are biased and hold an obvious conflict of interest. MiningStockEducation.com may provide website addresses or links to websites and we disclaim any responsibility for the content of any such other websites. The information you find on MiningStockEducation.com is to be used at your own risk. By reading MiningStockEducation.com, you agree to hold MiningStockEducation.com, its owner, associates, sponsors, affiliates, and partners harmless and to completely release them from any and all liabilities due to any and all losses, damages, or injuries (financial or otherwise) that may be incurred.
Data Science in 30 Minutes: Kirk Borne - A Fortuitous Career in Data Science
 
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In this webinar from August of 2017, renowned data scientist Kirk Borne took viewers on a journey through his career in science and technology and explained how the industry-and himself have evolved over the last 4 decades. Starting with skipping lunches in high school to a systematic twitter obsession, Kirk shed light on his road to success in the data science industry. The Data Incubator is a data science education company based in NYC, DC, and SF with both corporate training as well as recruiting services. For data science corporate training, we offer customized, in-house corporate training solutions in data and analytics. For data science hiring, we run a free 8 week fellowship training PhDs to become data scientists. The fellowship selects 2% of its 2000+ quarterly applicants and is free for Fellows. Hiring companies (including EBay, Capital One, Pfizer) pay a recruiting fee only if they successfully hire. You can read about us on Harvard Business Review, VentureBeat, or The Next Web, or read about our alumni at LinkedIn, Palantir or the NYTimes. http://thedataincubator.com About the speakers: Dr. Kirk Borne is a data scientist and an astrophysicist. He is Principal Data Scientist in the Strategic Innovation Group at Booz-Allen Hamilton since 2015. He was Professor of Astrophysics and Computational Science in the George Mason University (GMU) School of Physics, Astronomy, and Computational Sciences during 2003-2015. He served as undergraduate advisor for the GMU Data Science program and graduate advisor to students in the Computational Science and Informatics PhD program. Prior to that, he spent nearly 20 years supporting NASA projects, including NASA's Hubble Space Telescope as Data Archive Project Scientist, NASA's Astronomy Data Center, and NASA's Space Science Data Operations Office. He has extensive experience in large scientific databases and information systems, including expertise in scientific data mining. He was a contributor to the design and development of the new Large Synoptic Survey Telescope (LSST), for which he contributed in the areas of science data management, informatics and statistical science research, galaxies research, and education and public outreach. Michael Li founded The Data Incubator, a New York-based training program that turns talented PhDs from academia into workplace-ready data scientists and quants. The program is free to Fellows, employers engage with the Incubator as hiring partners. Previously, he worked as a data scientist (Foursquare), Wall Street quant (D.E. Shaw, J.P. Morgan), and a rocket scientist (NASA). He completed his PhD at Princeton as a Hertz fellow and read Part III Maths at Cambridge as a Marshall Scholar. At Foursquare, Michael discovered that his favorite part of the job was teaching and mentoring smart people about data science. He decided to build a startup to focus on what he really loves. Michael lives in New York, where he enjoys the Opera, rock climbing, and attending geeky data science events.
Views: 2494 The Data Incubator
Data Science- Data Science Using R&Tableau[2018]:Introduction to Data Science and Text Mining|ExcelR
 
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Data Science Using R&Tableau[2018]:Introduction to Data Science and Text Mining- #Data_Science #R #ExcelR_Solutions #Tableau #Introduction #2018 Data Science Tutorial for Beginners - #TextMining is the vastly used technique since a decade to gain information from the data we generate through various channels. As of now, #TextAnalysis is the hot new trend in #Analytics. So performing a text analysis will allow you to have the insight of search patterns, reviews on your product in a quantifiable manner. #StatisticalAnalysis & #MachineLearning are one of the key methods used for text mining, as it has become huge and mainly an untapped source of data. Watch our webinar session to have a complete understanding of Data Science & Text Mining. Certified Data Scientist Training Program: https://www.excelr.com/business-analytics/ Data Science Training : https://youtu.be/Ofn9a273OWE Things You Will Learn…. 1. Basics Statistics 2. Hypothesis Testing - What & How 3. Regression Analysis 4. Data Mining / Machine Learning 5. Test Mining & Natural Language Processing 6. Forecasting 7. Data Visualization 8. Tableau 9. R & R Studio 10. XLMiner 11. Minitab 12. Python For Detailed Course Content click here : https://www.excelr.com/business-analytics/ #datascience #datasciencetutorial #datascienceforbeginners #datasciencewithr #datasciencetutorialforbeginners #datasciencecourse ---------------------------------------------------------------------------------- Mode of Trainings : E-Learning Online Training Class Room Training --------------------------------------------------------------------------- For More Info Contact :: Toll Free (IND) : 1800 212 2120 | +91 80080 09706 Malaysia: 60 11 3799 1378 USA: 001-844-392-3571 UK: 0044 203 514 6638 AUS: 006 128 520-3240 Email: [email protected] Web: www.excelr.com
Top 5 Trends in Big Data Analytics You Need to Know | Big Data Analytics Trends -Career in Analytics
 
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#CareerInAnalytics | Know the top 5 trends in Big Data Analytics to be a successful data scientist and make a career in big data analytics. Know more about our analytics programs: PGP- Business Analytics: https://goo.gl/DmYrjK PGP-Big Data Analytics: https://goo.gl/JdrCec Business Analytics Certificate Program: https://goo.gl/MH4GCj #BigData #InternetOfThings #GreatLearning #GreatLakes #ArtificialIntelligence About Great Learning: - Great Learning is an online and hybrid learning company that offers high-quality, impactful, and industry-relevant programs to working professionals like you. These programs help you master data-driven decision-making regardless of the sector or function you work in and accelerate your career in high growth areas like Data Science, Big Data Analytics, Machine Learning, Artificial Intelligence & more. - Watch the video to know ''Why is there so much hype around 'Artificial Intelligence'?'' https://www.youtube.com/watch?v=VcxpBYAAnGM - What is Machine Learning & its Applications? https://www.youtube.com/watch?v=NsoHx0AJs-U - Do you know what the three pillars of Data Science? Here explaining all about the pillars of Data Science: https://www.youtube.com/watch?v=xtI2Qa4v670 - Want to know more about the careers in Data Science & Engineering? Watch this video: https://www.youtube.com/watch?v=0Ue_plL55jU - For more interesting tutorials, don't forget to Subscribe our channel: https://www.youtube.com/user/beaconelearning?sub_confirmation=1 - Learn More at: https://www.greatlearning.in/ For more updates on courses and tips follow us on: - Google Plus: https://plus.google.com/u/0/108438615307549697541 - Facebook: https://www.facebook.com/GreatLearningOfficial/ - LinkedIn: https://www.linkedin.com/company/great-learning/ - Follow our Blog: https://www.greatlearning.in/blog/?utm_source=Youtube Great Learning has collaborated with the University of Texas at Austin for the PG Program in Artificial Intelligence and Machine Learning and with UT Austin McCombs School of Business for the PG Program in Analytics and Business Intelligence.
Views: 2234 Great Learning
Big Big Changes For Stocks, Gold And Silver
 
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The changes that about to come will be so big so huge it will be devastating. The Charts I Use: Dow Jones Chart: https://tinyurl.com/ybnkqnoo Silver Chart: https://tinyurl.com/y8bbppat Crypto Charts: https://tinyurl.com/ydxxwogu About Me: ✅ Website - Apis Bull - http://www.apisbull.com ✅ Twitter - https://twitter.com/ApisBullTrading ✅ Donate - http://www.apisbull.com/donate Bitcoin 1FLn5bBJL7b14uzRdWTqAV1rftu5jcoTdp Ethereum and any Token 0x293521C8F9fEf583cd11786CA3561ce0Ca6a2E3f Dash Xy1Uxpeeki4DeRPfwGriUX3HTK6N57T7ds Litecoin LeVz71RTnKbTBiJBSh3dre9DgCuxKLwH6G ✅ I am not a financial adviser and this is not financial advice. I'm just a humble man with a great passion for all things stocks, commodities, block-chain, even tangible coins and technical charting. Donald Trump, collapse, David Morgan, Andy Hoffman, Rick Rule, Apis Bull Trading, Stock, market, gold, silver, coins, Steve St. Angelo, inflation, Mike Maloney, Greg Hunter, John Rubino, Nicholas Green, Digital Currency, Trace Mayer, James Turk, Peter Schiff, Hugo Salinas, Gerald Celente, Nomi Prins,, silver, Apis Bull Trading, stock, market, Rick Rule, David Morgan, silver, market crash, dollar collapse, dollar vigilante, Mike Maloney, Bo Polny, coins, futures, commodities, silver mines, bitcoin, irs, money, fiat, currency, silver mining, silver report, JP Morgan, Chase, Bank of America, Citi Bank, Wells Fargo, Bo Polny, jsnip4, manipulation Bix Wier, future money trends crush the street economy collapse Doug Casey gold coins silver eagles Financial News Silver News Gold RoadToRoota Road To Roota Kyle Bass Realist News Greg Mannarino Rob Kirby Reluctant PreppersThe Next News Info Wars Maneco64 Mike Maloney Gold Silver Eric Sprott Jim Rickards David Morgan Peter Schiff Max Keiser Robert Kiyosaki SilverDoctors Finance and Liberty Nomi Prins Jim Willie Cliff High Martin Armstrong Ron Paul Pastor Williams Bill Holter Bo Polny Jim Sinclair James Turk Key Financial Insights Web box Chris Dunn NADEX Ripple coinbase node investor zcash monero Jim Sinclair James Turk Web bot Silver News Gold Bix Weir RoadToRoota Road To Roota Kyle Bass Realist News Greg Mannarino Rob Kirby Reluctant Preppers The Next News Info Wars Maneco64 Mike Maloney Gold Silver Eric Sprottm Jim Rickards David Morgan Peter Schiff Max Keiser Robert Kiyosaki Silver Doctors Finance and Liberty Nomi Prins Jim Willie Clif High Martin Armstrong Ron Paul Pastor Williams Bill Holter Jim Sinclair James Turk Clif High. market trends,Dow Jones,Mike Maloney,Digital Currency, veritaseum, ethereum, bitcoin, money, currency, cryptocurrency, cryptocurrencies, trading, litecoin, Bo Polny, stocks, silver, gold, coins, tokens, cliff high,Bill Holter, Bix Wier, greg hunter, eos, dash, ripple, xrp, stellar, tron, cardano, monero, iota, nem, neo, zcash, omisego, electroneum, tenx, token tone vays zcoin. Donald Trump, collapse, Bo Polny, David Morgan, Andy Hoffman, Rick Rule, Apis Bull Trading, Stock, market, gold, silver, coins, Steve St. Angelo, inflation, Mike Maloney, Greg Hunter, John Rubino, Nicholas Green, Digital Currency, Trace Mayer, James Turk, Peter Schiff, Hugo Salinas, Gerald Celente, Nomi Prins,, silver, Apis Bull Trading, stock, market, Rick Rule, David Morgan, silver, market crash, dollar collapse, dollar vigilante, Mike Maloney, Bo Polny, coins, futures, commodities, silver mines, bitcoin, irs, money, fiat, currency, silver mining, silver report, JP Morgan, Chase, Bank of America, Citi Bank, Wells Fargo, manipulation ,Bix Weir, Bix Wier, future money trends crush the street economy collapse Doug Casey gold coins silver eagles Financial News Silver News Gold Bix Weir RoadToRoota Road To Roota Kyle Bass Realist News Greg Mannarino Rob Kirby Reluctant PreppersThe Next News Info Wars Maneco64 Mike Maloney Gold Silver Eric Sprott Jim Rickards David Morgan Peter Schiff Max Keiser Robert Kiyosaki SilverDoctors Finance and Liberty Nomi Prins Jim Willie Cliff High Martin Armstrong Ron Paul Pastor Williams Bill Holter Bo Polny Jim Sinclair James Turk Key Financial Insights Web box Chris Dunn NADEX Ripple coinbase node investor zcash monero Jim Sinclair James Turk Web bot Silver News Gold Bix Weir RoadToRoota Road To Roota Kyle Bass Realist News Greg Mannarino Rob Kirby Reluctant Preppers The Next News Info Wars Maneco64 Mike Maloney Gold Silver Eric Sprottm Jim Rickards David Morgan Peter Schiff Max Keiser Robert Kiyosaki Silver Doctors Finance and Liberty Nomi Prins Jim Willie Clif High Martin Armstrong Ron Paul Pastor Williams Bill Holter Bo Polny Jim Sinclair James Turk Clif High node investor veritaseum,ethereum,bitcoin,money,Bo Polny, stocks, silver,gold, coins,tokens,cliff high,Bill Holter,Bix Wier, greg hunter,eos,dash, monero, omisego,electroneum, tenx,token, tone vays, jsnip4 ,pillar,zcoin,x22 report,panic, charts,stock charts,inflation, jeff berwick,dollar vilante, node investor, collapse.
Views: 693 Apis Bull
The Path To Self-Service Analytics: A Success Story by Somesh Saxena, GE
 
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This talk was part of Dataiku's EGG NYC 2018 Conference. The Path To Self-Service Analytics: A Success Story by Somesh Saxena, Technical Product Manager at GE Aviation: The Self-Service Data program at General Electric Aviation has truly enabled the democratization of data and empowered business users to transform and analyze data through the implementation of data cataloging, workflow and visualization tools to drive horizontal outcomes and build data products for the digital industrial company. The program started in late 2016 when the Self-Service Data team from GE Aviation’s Digital Technology group rolled out the Self-Service Data tools. The team partnered with other organizations within the business, such as: engineering, supply chain, sales and marketing, and others, to identify and execute on projects within each group’s domain. Initial training sessions, and open office hours provided by the Self-Service Data team, helped user adoption and provided a sense of ease for non-technical users to work in the shared eco-system of GE’s data lake. Digital Data Analyst, an intensive week-long course teaching digital tools, data science and process excellence, was introduced in 2018. The training program was met with instant success, with over 700 graduates from multiple areas across the business. With a community of over 1,400 Self-Service developers building digital products to make data-driven decisions, the program is front and center of the digital cultural transformation at General Electric Aviation. Somesh Saxena is the Product Owner of Alation and Dataiku at General Electric Aviation. He manages a team of full-stack data engineers and helps lead the Self-Service Data program. Somesh is front and center of the digital cultural transformation at General Electric Aviation, training employees through the Digital Data Analyst training. He began his career with General Electric’s Digital Technology Leadership Program, where he led projects for the company’s customer portal, did full-stack web development in Cyber Security, and data ingestion, engineering and visualization in the data analytics space. Somesh is a Certified Scrum Product Owner from the Scrum Alliance. He holds a degree in Business Administration with a concentration in Information Systems from the University of Cincinnati.
Views: 122 Dataiku
Brief Look at Google Cloud AutoML Natural Language - its HIPAA Compliant!!
 
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Quick overview of Google's AutoML Natural Language Processing Cloud-based tool that allows you to do some serious supervised deep learning without writing one line of code! This series of AutoML tools are probably going to obsolete my job one day. MORE: Blog or code: http://www.viralml.com/video-content.html?fm=yt&v=UnDGPtHOaEk Signup for my newsletter and more: http://www.viralml.com Connect on Twitter: https://twitter.com/amunategui My books on Amazon: The Little Book of Fundamental Indicators: Hands-On Market Analysis with Python: Find Your Market Bearings with Python, Jupyter Notebooks, and Freely Available Data: https://amzn.to/2DERG3d Monetizing Machine Learning: Quickly Turn Python ML Ideas into Web Applications on the Serverless Cloud: https://amzn.to/2PV3GCV Grow Your Web Brand, Visibility & Traffic Organically: 5 Years of amunategui.github.Io and the Lessons I Learned from Growing My Online Community from the Ground Up: https://amzn.to/2JDEU91 Fringe Tactics - Finding Motivation in Unusual Places: Alternative Ways of Coaxing Motivation Using Raw Inspiration, Fear, and In-Your-Face Logic https://amzn.to/2DYWQas Create Income Streams with Online Classes: Design Classes That Generate Long-Term Revenue: https://amzn.to/2VToEHK Defense Against The Dark Digital Attacks: How to Protect Your Identity and Workflow in 2019: https://amzn.to/2Jw1AYS CMS Datasets: https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/Medicare-Provider-Charge-Data/Physician-and-Other-Supplier.html Google Documents: https://cloud.google.com/natural-language/automl/docs/ https://cloud.google.com/natural-language/automl/pricing Full script: Brief Look at Google Cloud AutoML Natural Language - its HIPAA Compliant!! Hello Friends In this video I am going to do a brief overview of Google's AutoML Natural Language Processing Cloud-based tool. It is in BETA but you can do some serious supervised deep learning without writing one line of code! This series of AutoML tools are probably going to obsolete my job one day. Either way I like to see this democratization of data science modeling tools as its going to let more people participate in the exploration and creation of predictive solutions. Best of all its HIPAA compliant! This is Manuel Amunategui, welcome to ViralML. Here is a quick look at the final result - the trained model and its predictive abilities. I downloaded data from the Centers for Medicare and Medicaid Services (CMS) consisting of millions of entries showing how much each doctor in the US charged Medicare, for what, and how much Medicare paid out. This data was made public starting in 2014 under the Affordable Care Act. CATEGORY:DataScience HASCODE:ViralML-AutoML-NLP-for-Healthcare-Presentation.html
Views: 226 Manuel Amunategui
Introduction to Business Analytics Training | Business Analytics Tutorial | Data Analytics
 
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In this video on Introduction to Business Analytics Training | Business Analytics Tutorial, we’ll be discussing the basics of business analytics and the concepts that will be covered in the data analytics certification program. • Meaning of business analysis • Importance of data • Evolution of an organisation in terms of data maturity • Concepts of business analytics, business intelligence, data mining • Structured analytics processes used for effective decision making • Characteristics of a good business analyst • Future of business analytics Advanced Business Analytics with R Certification Course https://www.manipalprolearn.com/data-science/advanced-business-analytics-with-r-certification-training?utm_source=YouTube&utm_medium=YouTube&utm_campaign=YouTube&utm_term=YouTube&utm_content=YouTube --------------------------------------------------------------------------------------------------- Use the coupon code YOUTUBE30 to avail exclusive discounts (YouTube Learners) --------------------------------------------------------------------------------------------------- --------------------------------------------------------------------------------------------------- Subscribe to our channel to get video updates. Hit the subscribe button above https://www.youtube.com/channel/UCllnb6S5fPzpVYcV8KYzhnA?view_as=subscriber?sub_confirmation=1 Also follow us on other channels Facebook: https://www.facebook.com/ManipalProLearn Twitter: https://twitter.com/manipalprolearn LinkedIn: https://www.linkedin.com/company/10147429 --------------------------------------------------------------------------------------------------- #businessanalytics #analyticstutorial #Rcertification About the Business Analytics Training Course The Advanced Business Analytics with R Certification Course is designed for fresh graduates and professionals who wish to embark on a career in data science. Led by industry experts, this training program includes 196 hours of learning, 3 hours of doubt clearing sessions and 8 case studies. --------------------------------------------------------------------------------------------------- Learning objectives of the Business Analytics Tutorial • Train candidates in the basics of business analytics • Use complex statistical tools for data analysis • Help you start your career in data analytics --------------------------------------------------------------------------------------------------- Why skills you’ll learn in this data Science with R Certification? • Solve complex problems using R • Use data sampling techniques to identify patterns and trends • Compute correlation between data series ---------------------------------------------------------------------------------------------------
Views: 189 Manipal ProLearn
Professor David Bell on Digital Marketing: Wharton Lifelong Learning Tour
 
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David Bell, the Xinmei Zhang and Yongge Dai Professor at the Wharton School, spoke to alumni in Los Angeles about managing brand and customer assets through digital marketing on the first stop of the Wharton Knowledge for Action Lifelong Learning tour.
Views: 41826 Wharton School
Scaling Deep Learning to 10,000 Cores and Beyond
 
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Deep learning and unsupervised feature learning offer the potential to transform many domains such as vision, speech, and natural language processing. However, these methods have been fundamentally limited by our computational abilities, and typically applied to small-sized problems. In this talk, P.h.D. candidate at Standford University, Quoc V Le, will describe the key ideas that enabled scaling deep learning algorithms to train a large model on a cluster of 16,000 CPU cores (2000 machines). This network has 1.15 billion parameters, which is more than 100x larger than the next largest network reported in the literature. Such network, when applied at the huge scale, is able to learn abstract concepts in a much more general manner than previously demonstrated. Specifically, Le finds that by training on 10 million By using these features, Le obtains breakthrough performance gains on several large-scale computer vision tasks.
Views: 6560 UW Video
Prof Ryan Baker, Data Science in Education, Part 2
 
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In this talk, Pof. Baker discusses how the methods of educational data mining draw from broader trends in data science, and some of the problems and methods more specific to education research. Throughout the talk, Baker discusses both the current state of the art in educational data mining, and some of the key research challenges and opportunities for data scientists working in this emerging area.
Views: 160 Shirin Mojarad
Text Analytics Future
 
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Text Analytics Future. #IIEX Interview with Anderson Analytics - OdinText founder Tom H. C. Anderson
Views: 395 OdinText
Lets Start Digital marketing course in hindi
 
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Let's create Your Future Digital With Digistaan. Join Our Advanced Digital Marketing Course. That will cover many Modules of Marketing And Digital Marketing like what is marketing, SEO, SEM, Email Marketing, Social Media Marketing, Affiliate Marketing , Digital Identity Creation, blogging, advanced analytics, blogging, video production, Photoshop, business Knowhow, etc To Know More Call +918527276655
Views: 567 Mr web technologies
Introduction to Jupyter Notebooks: The Open Source solution for developing & visualizing Python & R!
 
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Ever wanted to start learning Python, R and Data Science but unsure of how to get started or what tools to use? In this session, we will explain why Jupyter notebooks could be the ideal tool for you! We will explain the different ways it works in Windows vs Linux, what languages you can use (including Python, R, and Julia), and the demonstrate how writing code in Jupyter notebooks differs from standard coding GUIs. If you don't want to install yet more software on your PC, this session will also demonstrate how you can even use Jupyter Notebooks in Azure Cloud. Speaker Details: Ginger Grant provides consulting services in advanced analytic solutions, including machine learning, data warehousing, data visualization and cube development using the entire Microsoft Data Stack, including SQL Server, T-SQL, SSIS, SSAS, Power BI, and Azure. Ginger started working with data to solutions across a wide range of industries including insurance, education, healthcare, finance, and transportation. She is a prolific blogger at http://www.desertislesql.com and a frequent speaker and as an MCT provides training for training courses, at conferences and events worldwide to introduce more people to current developments and future trends in data. Microsoft has awarded her an MVP in Data Platform since 2016.
Cloudera Named Leader for Big Data and Spark in Cloud Report
 
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Sushant Rao, Director of Product Marketing for Cloud, shares how Cloudera’s data analytics and Spark platform empowers teams to develop and deploy data warehouse and machine learning in the cloud.
Views: 631 Cloudera, Inc.