This Project is an NLP project. In which it predicts the rating of a book review, by analyzing the review. Dataset used in this project - https://drive.google.com/drive/folders/1e4UT9sebo7VzwuXMjlg0RdES7s30DSfx?usp=sharing.

• Used relatively big data with 6,30,000 Reviews.
• Text Preprocessing : Tokenization, Lowercasing, Removing Punctuation, Removing Stopwords, Stemming or Lemmatization
• Feature Extraction : Bag-of-Words, TF-IDF, Word Embeddings ( Word2Vec )
• Building Models: Logistic Regression, RandomForestClassifier, XGBoostClassifier, GradientBoostingClassifier, AdaBoostClassifier, DecisionTreeClassifier, KNeighborsClassifier -Model Evaluation and Tuning: Finalized XGBoostClassifier and performed hyperparameter tuninig using RandomSearchCV
• Deployment: Webapp Using Streamlit library.
• App is live - https://huggingface.co/spaces/Suyash1302/Book_Review_Rating_Predictor