Chapter 8: Applying Machine Learning to Sentiment Analysis

Chapter Outline

• Preparing the IMDb movie review data for text processing

  • Obtaining the IMDb movie review dataset

  • Preprocessing the movie dataset into more convenient format

• Introducing the bag-of-words model

  • Transforming words into feature vectors

  • Assessing word relevancy via term frequency-inverse document frequency

  • Cleaning text data

  • Processing documents into tokens

• Training a logistic regression model for document classification

• Working with bigger data – online algorithms and out-of-core learning

• Topic modeling

  • Decomposing text documents with Latent Dirichlet Allocation

  • Latent Dirichlet Allocation with scikit-learn

• Summary

Please refer to the README.md file in ../ch01 for more information about running the code examples.