Goodreads Book Ratings Predictions

Notebook that predicts the rate of the book from using different machine learning models.

Language: Python

ML Library: Sikit-Learn

ML Type: Supervised -> Regression

Content:

1. Exploring Data.
2. Analyze Data through visualizations.
3. Data Preparation e.g.: [Ordinal Encoding, Handling Missing Values].
4. Feature Engineering.
5. Building Multiple Machine Learning Models.
6. Compare models accuracy on training data.
7. Make predictions using each model.
8. Compare models accuracy on test data.
9. Compare training VS test score for each model

Click Here to see the notebook on Kaggle

My Kaggle Account