MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 2.5 Hours | 989 MB
Genre: eLearning | Language: English
Use Python and the Twitter API to build your own sentiment analyzer!
Sentiment Analysis (or) Opinion Mining is a field of NLP that deals with extracting subjective information (positive/negative, like/dislike, emotions).
Learn why it's useful and how to approach the problem: Both Rule-Based and ML-Based approaches.
The details are really important - training data and feature extraction are critical. Sentiment Lexicons provide us with lists of words in different sentiment categories that we can use for building our feature set.
All this is in the run up to a serious project to perform Twitter Sentiment Analysis. We'll spend some time on Regular Expressions which are pretty handy to know as we'll see in our code-along.
Sentiment Analysis:
Why it's useful,
Approaches to solving - Rule-Based , ML-Based
Training & Feature Extraction
Sentiment Lexicons
Regular Expressions
Twitter API
Sentiment Analysis of Tweets with Python
Byte-Sized-Chunks Sentiment Analysis.part2.rar
Byte-Sized-Chunks Sentiment Analysis.part3.rar
Byte-Sized-Chunks Sentiment Analysis.part4.rar
Byte-Sized-Chunks Sentiment Analysis.part5.rar
Byte-Sized-Chunks Sentiment Analysis.part6.rar
TO MAC USERS: If RAR password doesn't work, use this archive program:
RAR Expander 0.8.5 Beta 4 and extract password protected files without error.
TO WIN USERS: If RAR password doesn't work, use this archive program:
Latest Winrar and extract password protected files without error.