Learning AI and machine learning online is difficult because the available resources are either too scattered or hidden behind paywalls. I just happened to find the AI/ML Bookshelf, an open-source book collection on GitHub, which brings together 13 classic AI and machine learning books that can be shared for free. It covers core topics such as deep learning interview questions, the fundamentals of large language models, reinforcement learning, and the mathematical foundations of machine learning, as well as cutting-edge content such as practical prompt word engineering and multi-agent reinforcement learning. GitHub: https://t.co/gRWqDR8FCA Each book comes with a brief introduction to help you quickly find the content you need. For example, "Deep Learning Interviews" includes over 400 carefully selected interview questions, while "Math4ml" uses intuitive examples to explain linear algebra and probability theory. All books are versions that the authors have allowed to share freely. They can be previewed directly on GitHub or downloaded to your local device for reading. Students who are learning AI can bookmark them for future reference.
