Learn how to perform sentiment analysis and emotion detection using TextBlob, NLTK, BERT, VADER, NRCLex, MultinomialNB
Sub Category
- Data Science
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Objectives
- Learn how to perform sentiment analysis on customer review data using TextBlob
- Learn how to analyze emotional aspect of customer reviews using EmoLex
- Learn how to perform sentiment analysis on twitter post data using VADER
- Learn how to analyze emotional aspect of tweets using NRCLex
- Learn how to predict sentiment of a tweet using BERT
- Learn how to predict sentiment of a tweet using Multinomial Naive Bayes
- Learn how to identify keywords that are frequently used in positive and negative customer reviews
- Learn how to find correlation between customer ratings and sentiment
- Case study: applying sentiment analysis on customer review dataset and predict if a review is more likely to be positive, negative or neutral
- Learn factors that contribute to bias in customer reviews
- Learn how to clean dataset by removing missing rows and duplicate values
- Learn the basic fundamentals of sentiment analysis and its practical applications
Pre Requisites
- No previous experience in sentiment analysis is required
- Basic knowledge in Python and NLP
FAQ
- Q. How long do I have access to the course materials?
- A. You can view and review the lecture materials indefinitely, like an on-demand channel.
- Q. Can I take my courses with me wherever I go?
- A. Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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