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TranslatedOpen-source manuscript of 《深入理解 AI Infra：量化分析与系统设计》 (In-Depth Understanding of AI Infra: Quantitative Analysis and System Design), by 李博杰 (Li Bojie): starting from hardware constraints and model architecture, it quantitatively derives the system design of LLM inference and training. Includes the full text of the book, a PDF, and companion calculation tools and experiments
Implementing LLM architectures from scratch in PyTorch
Train and Deploy an ML REST API to predict crypto prices, in 10 steps
TranslatedA basic tutorial for getting started with AI Agents from zero background. It is not just a tutorial but also an Agent that can run locally: read and write files, execute commands, MCP, long-term memory, with a built-in web interface to see every step clearly. Starting from a minimal 100-line loop, each lesson adds one capability, and in the end it breaks down mainstream Agents such as Claude Code and Codex