Project: Predicting Book Ratings with Sentiment Analysis and Neural Networks This project explores the use of Natural Language Processing (NLP) and neural networks to predict book ratings on Amazon.
Project Overview Data Preprocessing: The project utilizes the Amazon book reviews dataset. The reviews are preprocessed using the Natural Language Toolkit (NLTK) library. Preprocessing steps may include tokenization, removal of stop words, stemming/lemmatization, and text cleaning.
Sentiment Analysis: Sentiment analysis is performed on the preprocessed reviews to extract sentiment polarity (positive, negative, or neutral).
Neural Network: A neural network model is trained on the extracted features (sentiment scores and potentially other text-based features) to predict book ratings.
Evaluation: The model's performance is evaluated using metrics like accuracy. In this project, the achieved accuracy is 88%.