Linear-Algebra-Made-Easy---Learn-with-Python-and-Visualization

Why we included this project

Linear algebra is the math that machine learning quietly leans on, and this project teaches it the way most people actually learn best: by running code and looking at pictures. It is a two-volume Jupyter Notebook course from the Iris Series (鸢尾花书) by Dr. Ginger Jiang, covering 66 topics where each concept comes with runnable Python and figures instead of formulas alone. Working through the notebooks in order shows how vectors, matrices, eigenvalues, and decompositions really behave, which sticks better than a conventional textbook. It also works as a reference: when a data science idea feels fuzzy, the matching notebook gives you a visual, code-first explanation to revisit. This is study material, not a deployable tool, so expect a learning resource and a stock of ready-made visualization examples for your own teaching。