In this course, you'll learn specialized techniques for feature selection and extraction to improve machine learning models. Through practical applications on a synthetic dataset, you'll discover how to identify and remove low-variance features, use correlation with the target variable, and apply advanced selection methods to refine your datasets for optimal efficiency and effectiveness.
Overview
Syllabus
- Lesson 1: Mastering Variance-Based Feature Selection with VarianceThreshold in Python
- Lesson 2: Unveiling the Power of Univariate Feature Selection with SelectKBest in Python
- Lesson 3: Mastering Feature Selection with Mutual Information in Python
- Lesson 4: Mastering Feature Selection with Recursive Feature Elimination in Python
- Lesson 5: Mastering Feature Selection with SelectFromModel in Scikit-learn
