Book7_Visualizations-for-Machine-Learning

Why we included this project

This seventh volume of the Iris Series (鸢尾花书) carries on the project's habit of teaching with pictures rather than walls of equations, walking readers from basic arithmetic up through real machine learning. Thousands of hand-drawn vector graphics and runnable Jupyter notebooks turn the mechanics of regression and Bayesian inference into something you can actually step through line by line. It suits self-learners, instructors hunting for lecture illustrations, and engineers who want to firm up the math behind models they already use. Since every figure is generated from Python code, you can copy an example, tweak it, and rerun it to test your own understanding instead of just reading along. The repo openly invites corrections, even offering free books to readers who catch the most errors, which keeps the material under steady community review。