B2.1 Getting Started with Feature Selection in scikit-learn

B2. Reducing Dimensions in Data with scikit-learn. Getting Started with Feature Selection in scikit-learn: 01. Module Overview 02. Prerequisites and Course Outline 03. The Curse of Dimensionality 04. Overfitted Models and Data Sparsity 05. Exploring Techniques for Reducing Dimensions 06. Demo - Exploring the Classification Dataset 07. Demo - Performing Classification with All Features 08. Demo - Exploring the Regression Dataset 09. Demo - Performing Kitchen Sink Regression Using ML and Non-ML Techniques 10. Feature Selection and Dictionary Learning 11. Demo - Using Univariate Linear Regression Tests to Select Features 12. Demo - Defining Helper Functions to Build and Train Multiple Models with D 13. Demo - Finding the Best Value of K 14. Demo - Using Mutual Information to Select Features 15. Demo - Dictionary Learning to Find Sparse Representations of Data 16. Summary