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
Using discussion forums
Please use the discussion forums on this course to engage with other students and to help each other out. Unfortunately, much as we would like to, it is not possible for us at Loonycorn to respond to individual questions from students:-(
We're super small and self-funded with only 2 people developing technical video content. Our mission is to make high-quality courses available at super low prices.
The only way to keep our prices this low is to *NOT offer additional technical support over email or in-person*. The truth is, direct support is hugely expensive and just does not scale.
We understand that this is not ideal and that a lot of students might benefit from this additional support. Hiring resources for additional support would make our offering much more expensive, thus defeating our original purpose.
100% Off Udemy Coupon Code - https://www.udemy.com/sentiment-analysis/?couponCode=OCTOBER_2017
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