This repository contains the draft manuscripts and code files that accompany the Elsevier publication Machine Learning Made Visual with Python.
”数学不难“ 之 《概率统计不难》; source: https://github.com/Visualize-ML/Probability-and-Statistics-Made-Easy---Learn-with-Python-and-Visualization.git
Book_7_《机器学习》 | 鸢尾花书:从加减乘除到机器学习; source: https://github.com/Visualize-ML/Book7_Visualizations-for-Machine-Learning.git
Book_6_《数据有道》 | 鸢尾花书:从加减乘除到机器学习; source: https://github.com/Visualize-ML/Book6_First-Course-in-Data-Science.git
Book_5_《统计至简》 | 鸢尾花书:从加减乘除到机器学习;source: https://github.com/Visualize-ML/Book5_Essentials-of-Probability-and-Statistics.git
Book_4_《矩阵力量》 | 鸢尾花书:从加减乘除到机器学习;source: https://github.com/Visualize-ML/Book4_Power-of-Matrix.git
Book_3_《数学要素》 | 鸢尾花书:从加减乘除到机器学习;source:https://github.com/Visualize-ML/Book3_Elements-of-Mathematics.git
Book_2_《可视之美》 | 鸢尾花书:从加减乘除到机器学习, source: https://github.com/Visualize-ML/Book2_Beauty-of-Data-Visualization.git
Book_1_《编程不难》 | 鸢尾花书:从加减乘除到机器学习, source: https://github.com/Visualize-ML/Book1_Python-For-Beginners.git
”数学不难“ 之 《线性代数不难》上下册,66话题完册,source: https://github.com/Visualize-ML/Linear-Algebra-Made-Easy---Learn-with-Python-and-Visualization.git
Optimal Transport for Machine Learners. Mirrors from https://github.com/gpeyre/ot4ml.git
Mirrors from https://github.com/openclaw/clawdbot-ansible.git
Mirrors from https://github.com/affaan-m/everything-claude-code.git
Mirrors from https://github.com/zstmfhy/zlibrary-to-notebooklm.git
合并https://repo.or.cz/light-and-matter.git及https://github.com/npettiaux/lightandmatter.git两个仓库的修订日志
Source files for the text Introductory Statistics for the Life and Biomedical Sciences. Mirrors from https://github.com/dave-harrington/oi_biostat_text.git