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Introduction to Text Analytics with R: Overview
 
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The overview of this video series provides an introduction to text analytics as a whole and what is to be expected throughout the instruction. It also includes specific coverage of: – Overview of the spam dataset used throughout the series – Loading the data and initial data cleaning – Some initial data analysis, feature engineering, and data visualization About the Series This data science tutorial introduces the viewer to the exciting world of text analytics with R programming. As exemplified by the popularity of blogging and social media, textual data if far from dead – it is increasing exponentially! Not surprisingly, knowledge of text analytics is a critical skill for data scientists if this wealth of information is to be harvested and incorporated into data products. This data science training provides introductory coverage of the following tools and techniques: – Tokenization, stemming, and n-grams – The bag-of-words and vector space models – Feature engineering for textual data (e.g. cosine similarity between documents) – Feature extraction using singular value decomposition (SVD) – Training classification models using textual data – Evaluating accuracy of the trained classification models Kaggle Dataset: https://www.kaggle.com/uciml/sms-spam-collection-dataset The data and R code used in this series is available here: https://code.datasciencedojo.com/datasciencedojo/tutorials/tree/master/Introduction%20to%20Text%20Analytics%20with%20R -- Learn more about Data Science Dojo here: https://hubs.ly/H0hz5_y0 Watch the latest video tutorials here: https://hubs.ly/H0hz61V0 See what our past attendees are saying here: https://hubs.ly/H0hz6-S0 -- At Data Science Dojo, we believe data science is for everyone. Our in-person data science training has been attended by more than 4000+ employees from over 800 companies globally, including many leaders in tech like Microsoft, Apple, and Facebook. -- Like Us: https://www.facebook.com/datasciencedojo Follow Us: https://twitter.com/DataScienceDojo Connect with Us: https://www.linkedin.com/company/datasciencedojo Also find us on: Google +: https://plus.google.com/+Datasciencedojo Instagram: https://www.instagram.com/data_science_dojo Vimeo: https://vimeo.com/datasciencedojo
Views: 73871 Data Science Dojo
Text Analysis - Segmentation & Topic Modeling (part1)
 
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WIDM lab tutorial in 2016 Speaker: Showmin
Views: 208 Hsiu-Min Chuang
Presentation @ Text Analytics World 2013
 
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While there is great value locked deep in companies' textual assets, mining this information can be both time consuming and expensive. These costs often serve as a barrier to entry, preventing companies from capitalizing on the business value inherent in text. Fortunately, there are many tools available which can help you begin to transform this unstructured data into actionable intelligence. Through case study examples, this session will explore multiple technologies, including MapReduce, which can be used to tackle many typical text mining problems, help you discover the possibilities buried in your text and boost your business case.
Views: 187 Janine Johnson
Lecture1 - Introduction to Text Mining - Part 2
 
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This talk, named "Introduction to Text Mining", was delivered by Prof. Mandar Mitra at "Text Mining Workshop - 2014", organized by ACM Student Chapter, ISI Kolkata. This is part 2 of the lecture.
Views: 267 Abhirup Banerjee
How to run the text mining (tm) package in R
 
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Link to the article http://goo.gl/w24W2 . Link to the script http://goo.gl/gpUYR
Views: 17489 resinnovstation
Data Preprocessing Segment Data - Use Pandas Sklearn Machine Learning to Analyze Stock Market 03
 
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Use Pandas Sklearn Machine Learning to Analyze Stock Market 03 Udacity Machine Learning Nanodegree Capstone project Byte size videos : 03 Data Preprocessing Segmenting Data, extract stock price data
Views: 323 Uniqtech