The aim of this project is to investigate the efficacy of different Supervised Machine Learning algorithms on performing Sentiment Analysis i.e, tagging randomly selected Amazon Product reviews as Positive or Negative.
The dataset 'Consumer reviews of Amazon Products' has been taken from data.world - https://data.world/datafiniti/consumer-reviews-of-amazon-products.
It consists of 28,332 observations and 24 columns and has reviews from different categories like Electronics, Health & Beauty, Toys & Games and Office Supplies.
The attributes used for this project are review text and review ratings.
- Python
- Pandas
- re
- nltk
- scikit-learn
- Naive Bayes
- Decision Trees
- Support Vector Machine