[AI Minor News Flash] All-in-One Learning Compendium for Math, CS, and AI Launches on GitHub

📰 News Summary

• A new repository titled “Compendium” has been released, encapsulating extensive knowledge in mathematics (vector spaces, calculus, statistics), machine learning, and computer science.
• Currently available sections include linear algebra, calculus, statistics, probability, and both classical and deep learning.
• Advanced topics such as natural language processing (NLP), computer vision, GPU programming, and system design are set to be rolled out gradually.

💡 Key Points

• Essential mathematical foundations for AI development (like SVD decomposition and gradient descent) are presented in a well-organized manner by concept.
• The structure covers not only theory but also practical aspects like distributed training, reinforcement learning, and hardware-related optimizations such as SIMD and GPU programming (CUDA/Triton).

🦈 Shark’s Eye (Curator’s Perspective)

For engineers swimming through the vast ocean of knowledge, this is the ultimate treasure map! Especially impressive is the effort to unify the “skeleton of AI” from vector spaces and linear transformations to cutting-edge techniques like MoE (Mixture of Experts) and diffusion models. While many sections are still “Coming soon,” the planned inclusions of hardware-related optimizations like SIMD and CUDA are sure to be a hit for sharks looking to boost their implementation skills!

🚀 What’s Next?

With seamless connections from basics to applications, this repository could serve as a standard curriculum for aspiring AI engineers. As unpublished sections get filled in, it will evolve into an even more powerful reference site.

💬 A Shark’s Takeaway

Math is like a shark’s teeth; the sharper they are, the easier it is to catch your prey (or tackle challenges)! Sharpen your skills with this repository! 🦈🔥

📚 Terminology

• Compendium: A concise summary or overview that compiles comprehensive knowledge within a specific field. A knowledge treasure trove.

• SIMD: A technology that processes multiple data points simultaneously with a single instruction, essential for high-speed image processing and AI computations.

• Inference: The process of making predictions or decisions on new data using a trained model.

• Source: Maths, CS and AI Compendium