wx-chevalier/Mathematics-Notes
:books: [.md & .ipynb] 人工智能与深度学习实战--数理统计与数据分析篇
This project provides comprehensive notes and practical examples on the mathematical foundations required for artificial intelligence and data analysis. It covers core topics from basic calculus and linear algebra to probability, statistics, optimization, and numerical methods. Data scientists, machine learning engineers, and researchers can use this resource to deepen their understanding of the underlying mathematics behind complex algorithms.
Use this if you are a data professional, AI practitioner, or student who needs a structured and in-depth reference for the mathematical concepts critical to advanced data analysis and machine learning.
Not ideal if you are looking for an introduction to programming or a quick-start guide to using specific AI libraries without delving into the theoretical mathematical background.
Stars
39
Forks
11
Language
Jupyter Notebook
License
—
Category
Last pushed
Mar 15, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/wx-chevalier/Mathematics-Notes"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Compare
Related frameworks
harvard-edge/cs249r_book
Machine Learning Systems
wx-chevalier/AI-Notes
:books: [.md & .ipynb] Series of Artificial Intelligence & Deep Learning, including Mathematics...
datawhalechina/key-book
《机器学习理论导引》（宝箱书）的证明、案例、概念补充与参考文献讲解。
rickiepark/handson-ml3
<핸즈온 머신러닝 3판>의 주피터 노트북 저장소
Ceyron/machine-learning-and-simulation
All the handwritten notes 📝 and source code files 🖥️ used in my YouTube Videos on Machine...