Alexis BAYLET
d35d4c964b
- Introduced Chapter 0: Introduction to Statistical Estimation with foundational concepts and methods. - Added Chapter 1: Non-Parametric Density Estimation covering kernel methods and performance analysis. - Included Chapter 2: Theory of Regression focusing on non-parametric methods and regularization techniques. - Implemented Chapter 3: Neural Networks as Approximators discussing the limitations of linear approximation methods. - Added corresponding PDF files for each chapter.
230 KiB
230 KiB