Open-Sourced AI/ML Systems Learning Repository
techNmak · x · 2026-07-13
This is a GitHub repository dedicated to deep learning in **AI/ML**. The author emphasizes that it is not a "quick-start tutorial" but a long-term project thoroughly explaining fundamental concepts. ### Main Contents - Math Foundations: Vectors, Matrices, Calculus, Statistics, Probability - Machine Learning: Classic ML, Distributed Training, RL - NLP / LLM: Transformer, Attention, MoE, SSM, LLM Architecture - Computer Vision: Diffusion, Flow Matching, ViT, SLAM - Audio & Speech: ASR, TTS, WaveNet, Conformer, Speaker Diarization - Multimodal: CLIP, VLM, Image/Video Tokenization, World Models - Autonomous Systems: VLA, Autonomous Driving, Spatial Robotics - GPU/Inference/Systems: CUDA, Triton, ARM NEON, AVX, TPU, WebGPU, Quantization, Inference Optimization ### Additional Features - Covers roughly 20 chapters. - Only requires basic math and Python as prerequisites. - Includes a built-in **MCP server**, allowing it to be used as a knowledge base by Claude Code, Cursor, and VS Code. The author also mentions that these notes have helped friends prepare for interviews at DeepMind, OpenAI, and Nvidia.
Related event: Open-Source Systematic Learning Repository for AI/ML Research Engineers(2 posts)→
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