Lihang is an open-source repository that provides educational notes, mathematical derivations, and code implementations based on the book Statistical Learning Methods by Li Hang. The repository aims to help readers understand the theoretical foundations of machine learning algorithms through practical implementations and detailed explanations. It includes notebooks and scripts that demonstrate how key algorithms such as perceptrons, decision trees, logistic regression, support vector machines, and hidden Markov models work in practice. In addition to code examples, the project contains supplementary materials such as formula references, glossaries of technical terms, and documentation explaining mathematical notation used throughout the algorithms. The repository also provides links to related research papers and references that expand on the theoretical background presented in the book.
Features
- Implementation of machine learning algorithms from the Statistical Learning Methods textbook
- Mathematical derivations and explanations of algorithm foundations
- Jupyter notebooks and Python scripts demonstrating algorithm behavior
- Reference materials including symbol indexes and glossaries
- Supporting documentation and references for deeper study
- Educational framework linking theory with practical machine learning code