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ML_pipeline

Welcome to our github for the ML project: we will explain how the project works if you want to see some exploratory analysis try to see the EDA for good insights. if you want to train the model you can add the data with the same structure as books.csv and launch the train file and everything will work if you want to predict with new data you need just to respect our train model, which means use the preprocessing part and then add your new data then boom you have your prediction

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Utilizing data from Goodreads, this ML pipeline leverages advanced preprocessing, feature engineering, and models like Lasso Regression, RandomForest, and XGBoost to predict book ratings and uncover patterns in reader perceptions.

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