Build an automated system for analyzing text documents and finding the polarity of the documents. This course delves into the evolving area of sentiment analysis. The course starts with the basics of sentiment analysis and natural language processing and covers both lexicon based approach and machine learning based methods of sentiment analysis. By the end of this course you will be conversant with popular python libraries such as NLTK, VADER, TextBlob and Sklearn and should be able to build a sophisticated sentiment analyzer with reasonable accuracy.
You can expect to gain the following skills from this course
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Data mining using web-scraping
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Natural language processing basics
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Lexicon based sentiment analysis
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Machine learning based sentiment analysis
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Using VADER and TextBlob libraries to perform sentiment analysis
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Naive Bayes algorithm
- Building machine learning based sentiment analyzer
Course image by courtesy of rawpixel.com
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