In summary, this session covered some topics, including data preparation, exploratory data analysis, the validation framework, linear regression model, LR vector and normal forms, the baseline model, root mean squared error, feature engineering, regularization, tuning the model, and using the best model with new data. All these concepts were explained using the problem to predict the price of cars.
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