This project provides a Chinese translation of "Machine Learning: A Probabilistic Perspective" by Kevin P. Murphy, alongside Python implementations of the algorithms and models discussed in the book. It aims to serve as a learning resource for individuals studying probabilistic machine learning, offering both conceptual understanding through translation and practical application via code.

How It Works

The project translates the book's content into Chinese, with figures annotated to link to corresponding code files found in the MLAPP-CODE directory. The Python implementations cover various algorithms and models from the book, facilitating hands-on learning and experimentation. The project also includes explanations of key code modules and interpretations of related research papers.

Quick Start & Requirements

• Installation: Code is available in the MLAPP-CODE folder.
• Prerequisites: Python. Specific versions or additional libraries are not explicitly stated but are implied by the nature of machine learning implementations.
• Resources: No specific hardware or resource requirements are mentioned.
• Documentation: https://qiguming.github.io/

Highlighted Details

• Covers the 2021 edition of MLAPP, including expanded deep learning content and recent research areas like self-supervised learning.
• Features blog posts interpreting research papers from OpenAI researchers.
• Includes recent updates on diffusion models and information theory.
• Addresses issues like formula rendering problems and provides navigation aids like glossaries and content guides.

Maintenance & Community

The project shows recent activity, with updates spanning from 2021 to early 2025, indicating ongoing development and translation efforts. Specific community channels or contributor details are not provided in the README.

Licensing & Compatibility

The README does not specify a license. This lack of explicit licensing information may pose compatibility issues for commercial use or integration into closed-source projects.

Limitations & Caveats

Some formula rendering issues were previously noted, and certain translations or expressions may require adjustment. The project's scope is primarily focused on the Chinese translation and Python implementations, with limited information on broader community support or formal testing.