- Created an Machine learning model that analyze the product reviews and classify them into Positive or Negative tag.
- Represented pre-processed data using feature selection techniques like Term Frequency-Inverse Document Frequency (TF–IDF).
- Used classifiers like Decision Tree, Support Vector Machine and Naive bayes to classify sentiments of data.
- Took the Book Review’s Data of Amazon from here.
- It contains 10000 reviews including reviewerID, reviewerName, helpful, reviewText, overall, summary, reviewTime, etc.
- Out of which I only kept required field reviewText and overall (rating) for Analysis.