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In this course, you will :
- focuses on the fundamentals of model validation From dividing data into training, validation, and testing datasets to developing an understanding of the bias-variance tradeoff, we lay the groundwork for the K-Fold and Leave-One-Out validation techniques used in chapter three.
- focuses on cross-validation in order to validate model performance
- discover more about hyperparameter tuning After all, model validation enables tuning and aids in the selection of the best overall model.
Syllabus :
- Basic Modeling in scikit-learn
- Validation Basics
- Cross Validation
- Selecting the best model with Hyperparameter tuning.
