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Building Sentiment Analysis Systems in Python
Online opinions are becoming ubiquitous - more people are expressing their views online than ever before. As a result, extracting sentiment information from these opinions is becoming very important. In this course, Building Sentiment Analysis Systems in Python, you will learn the fundamentals of building a system to do so in Python. First, you will learn the differences between ML- and rule-based approaches, and how to use VADER, Sentiwordnet, and Naive Bayes classifiers. Next, you will build three sentiment analyzers, and use them to classify a corpus of movie reviews made available by Cornell. Finally, you will gain a conceptual understanding of Support Vector Machines, and why Naive Bayes is usually a better choice. When you're finished with this course, you will have a clear understanding of how to extract sentiment from a body of opinions, and of the design choices and trade-offs involved.
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Length | 2.5 hours |
Starts | On Demand (Start anytime) |
Cost | $29/month (Access to entire library- free trial available) |
From | Pluralsight |
Instructor | Vitthal Srinivasan |
Download Videos | On Windows, MacOS, iOS, and Android Pluralsight app |
Language | English |
Subjects | Programming Data Science IT & Networking |
Tags | Machine Learning Data Professional Sentiment Analysis |
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Rating | Not enough ratings |
---|---|
Length | 2.5 hours |
Starts | On Demand (Start anytime) |
Cost | $29/month (Access to entire library- free trial available) |
From | Pluralsight |
Instructor | Vitthal Srinivasan |
Download Videos | On Windows, MacOS, iOS, and Android Pluralsight app |
Language | English |
Subjects | Programming Data Science IT & Networking |
Tags | Machine Learning Data Professional Sentiment Analysis |
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