Geometry of Regression Model and Feature Engineering

Explore the geometric aspects of regression models and delve into feature engineering in this 27-minute lecture. Learn how basis expansion in mathematical statistics relates to feature engineering in machine learning. Discover techniques for transforming original data into higher dimensions to find better linear hyper-plane fits, potentially revealing non-linear relationships between feature spaces and target variables. Examine practical examples that illustrate these concepts and their applications in data analysis and predictive modeling.