// the find
Visualize-ML/Book7_Visualizations-for-Machine-Learning
Book_7_《机器学习》 | 鸢尾花书：从加减乘除到机器学习；欢迎批评指正
This is the code companion to Book 7 of the 鸢尾花书 (Iris Flower Book) series, a Chinese-language machine learning textbook. Each chapter folder pairs a PDF (the book text) with Jupyter notebooks that implement the corresponding topic, from linear regression through Bayesian methods, SVMs, PCA, and clustering. It's for someone learning ML fundamentals from the ground up who reads Chinese, not for people looking for a reusable library.
The chapter-to-notebook mapping is unusually complete — 25 chapters, each with runnable code that mirrors the math in the accompanying PDF, which is rare for textbook repos that usually give you scattered snippets. A handful of chapters (KNN, decision trees, PCA, hierarchical/density clustering) ship Streamlit apps instead of static notebooks, so you can actually play with the parameters instead of just reading plots. 3.3k stars and 638 forks suggest real usage, not just a personal notes dump.
The README is just a list of discount links to the author's Zhihu paywall for other books in the series — there's no setup instructions, no requirements.txt, no explanation of what's in the repo for someone landing here without context. Everything is Chinese-only, so it's a non-starter if you don't read the language, and there's no English fork or translation linked. It's structured as book supplementary material, not a library: no package to install, no API, no tests, and the code likely won't run without manually figuring out which pickled/CSV data files each notebook expects.