- Mathematics for Machine Learning
- Algebra, Topology, Differential Calculus, and Optimization Theory for Computer Science and Machine Learning
- Linear Algebra and Optimization with Applications to Machine Learning
- Numerical Recipes
- Numerical Optimization
- Convex Optimization
- Numerical Analysis
- An Introduction to Statistical Learning
- The Elements of Statistical Learning
- 统计学习方法
- The Nature of Statistical Learning Theory
- Statistical Learning Theory
- Python for Data Analysis
- Coursera: AI for Everyone
- UC Berkeley CS188: Introduction to Artificial Intelligence
- Stanford CS221: Artificial Intelligence: Principles and Techniques
- Kaggle: Intro to Machine Learning
- Kaggle: Intermediate Machine Learning
- Kaggle: Feature Engineering
- Stanford CS 229 Cheatsheets
- Coursera: Machine Learning Specialization
- Coursera: Machine Learning in Production
- Stanford CS229: Machine Learning
- Stanford CS228: Probabilistic Graphical Models
- NTU by Hung-Yi Lee: Machine Learning
- Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems
- Machine Learning Yearning
- Pattern Recognition and Machine Learning
- Probabilistic Machine Learning Book Series
- 机器学习
- 南瓜书PumpkinBook
- Probabilistic Graphical Models: Principles and Techniques
- Foundations of Machine Learning
- Probably Approximately Correct
- Coursera: Deep Learning Specialization
- Stanford CS230: Deep Learning
- MIT 6.S191 Introduction to Deep Learning
- fast.ai: Practical Deep Learning for Coders
- CMU 10-414/714: Deep Learning Systems: Algorithms and Implementation
- DeepMind x UCL: The Deep Learning Lecture
- Deep Learning with Python
- Deep Learning
- Dive into Deep Learning
- Understanding Deep Learning
- Deep Learning: Foundations and Concepts
- Stanford CS224n: Natural Language Processing with Deep Learning
- Stanford CS224d: Deep Learning for Natural Language Processing
- Foundations of Statistical Natural Language Processing
- Speech and Language Processing
- Introduction to Information Retrieval
- UC Berkeley CS285/294 Deep Reinforcement Learning
- DeepMind x UCL: Introduction to Reinforcement Learning with David Silver
- Stanford CS234: Reinforcement Learning
- Attention Is All You Need
- The Llama 3 Herd of Models
- Hugging Face: NLP Course
- Hugging Face: Conceptual Guides of Transformer
- Microsoft: Generative AI for Beginners - A Course
- Cohere: LLM University - Large Language Models
- LLM101n
- Coursera: Generative AI for Everyone
- DeepLearning.AI: ChatGPT Prompt Engineering for Developers
- DeepLearning.AI: Building Systems with the ChatGPT API
- Coursera: Generative AI with Large Language Models
- Stanford CS25: Transformers
- Stanford CS324: Large Language Models
- DeepLearning.AI: LangChain for LLM Application Development