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Summary
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Classroom Contents
Machine Learning Applications
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- 1 Introduction
- 2 Agenda
- 3 Introduction to Text Mining
- 4 Applications of Text Mining
- 5 Various Text Mining techniques
- 6 Challenges of Text Mining
- 7 Understanding text transformations
- 8 Working with raw text
- 9 Using Count Vectorizer
- 10 Understanding TF/IDF in Text Mining
- 11 Model building using Logic Regression
- 12 Summary
