AI-Notes and Mathematics-Notes
About AI-Notes
wx-chevalier/AI-Notes
:books: [.md & .ipynb] Series of Artificial Intelligence & Deep Learning, including Mathematics Fundamentals, Python Practices, NLP Application, etc. 💫 人工智能与深度学习实战，数理统计篇 | 机器学习篇 | 深度学习篇 | 自然语言处理篇 | 工具实践 Scikit & Tensoflow & PyTorch 篇 | 行业应用 & 课程笔记
This project offers a comprehensive collection of notes and practical examples for understanding and applying Artificial Intelligence, Machine Learning, and Deep Learning concepts. It takes in theoretical foundations and code examples, primarily in Jupyter Notebooks, to provide clear explanations and practical implementations. Data scientists, machine learning engineers, and students looking to master AI applications will find this resource invaluable.
About Mathematics-Notes
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.
Related comparisons
Scores updated daily from GitHub, PyPI, and npm data. How scores work