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Goodreads Rating Predictions

This project was created as part of the Python Machine Learning Labs course at DSTI - School of Engineering during the Spring 2024 Rentrée.

This is a Kedro project. All content is located within the goodreads-predictor directory. Please see the README in that directory (within the kedro project) for more details.

NOTICES:

  • Any kedro terminal commands must be run from within the goodreads-predictor directory
  • It is essential that pandas 2.2.2 or greater is used (We recommend starting with a fresh environment for this project)
  • The model training pipelines can be taxing on computer resources. To avoid this, the project_summary notebook has a summarized process and results walkthrough that does not require you to run this model
  • Model results may be slightly different between runs of the modeling pipelines

About

Using machine learning to predict Goodreads ratings utilizing the Kedro framework. Includes EDA, rich feature engineering and data integration, model building with pipelines, and model comparison

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