luwill/Machine_Learning_Code_Implementation
A companion code repository for a Chinese ML textbook, implementing 26 classical machine learning algorithms with mathematical derivations and pure Python code.
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This repository accompanies a Chinese machine learning textbook (based on Li Hang’s Statistical Learning Methods and Zhou Zhihua’s Machine Learning), offering clean Python implementations of 26 classic algorithms across four categories: single-model supervised learning, ensemble supervised learning, unsupervised learning, and probabilistic models. The code is organized by chapter and written in Jupyter Notebooks, serving as supplementary material for readers learning algorithm theory and implementation.
Frequently asked
- What is luwill/Machine_Learning_Code_Implementation?
- A companion code repository for a Chinese ML textbook, implementing 26 classical machine learning algorithms with mathematical derivations and pure Python code.
- Is Machine_Learning_Code_Implementation open source?
- Yes — luwill/Machine_Learning_Code_Implementation is an open-source project tracked on heatdrop.
- What language is Machine_Learning_Code_Implementation written in?
- luwill/Machine_Learning_Code_Implementation is primarily written in Jupyter Notebook.
- How popular is Machine_Learning_Code_Implementation?
- luwill/Machine_Learning_Code_Implementation has 1.5k stars on GitHub.
- Where can I find Machine_Learning_Code_Implementation?
- luwill/Machine_Learning_Code_Implementation is on GitHub at https://github.com/luwill/Machine_Learning_Code_Implementation.