In this video we'll be building our own Twitter Sentiment Analyzer in just 14 lines of Python. It will be able to search twitter for a list of tweets about any topic we want, then analyze each tweet to see how positive or negative it's emotion is.
The coding challenge for this video is here:
https://github.com/llSourcell/twitter_sentiment_challenge
Naresh's winning code from last episode:
https://github.com/Naresh1318/GenderClassifier/blob/master/Run_Code.py
Victor's Runner up code from last episode:
https://github.com/Victor-Mazzei/ml-gender-python/blob/master/gender.py
I created a Slack channel for us, sign up here:
https://wizards.herokuapp.com/
More on TextBlob:
https://textblob.readthedocs.io/en/dev/
Great info on Sentiment Analysis:
https://www.quora.com/How-does-sentiment-analysis-work
Great sentiment analysis api:
http://www.alchemyapi.com/products/alchemylanguage/sentiment-analysis
Read over these course notes if you wanna become an NLP god:
http://cs224d.stanford.edu/syllabus.html
Best book to become a Python god:
https://learnpythonthehardway.org/
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https://www.patreon.com/user?u=3191693
Two Minute Papers Link:
https://www.youtube.com/playlist?list=PLujxSBD-JXgnqDD1n-V30pKtp6Q886x7e
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