- 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.
