What You Will Learn!
- Design and Implement a sentiment analysis measurement system in Python
- Grasp the theory underlying sentiment analysis, and its relation to binary classification
- Identify use-cases for sentiment analysis
Description
Note: This course is a subset of our 20+ hour course 'From 0 to 1: Machine Learning & Natural Language Processing' so please don't sign up for both:-)
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
Who Should Attend!
- Nope! Please don't enroll for this class if you have already enrolled for our 21-hour course 'From 0 to 1: Machine Learning and NLP in Python'
- Yep! Analytics professionals, modelers, big data professionals who haven't had exposure to machine learning
- Yep! Engineers who want to understand or learn machine learning and apply it to problems they are solving
- Yep! Tech executives and investors who are interested in big data, machine learning or natural language processing
- Yep! Product managers who want to have intelligent conversations with data scientists and engineers about machine learning
TAKE THIS COURSE