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TranslatedA beginner's bible for AI that doesn't play at being obscure or cater to a niche few, easy to grasp for everyone from students to engineers. It covers neural networks to large models, top-level design to micro-level principles, and engineering implementation to algorithm fundamentals. After studying it, you will thoroughly understand why the seemingly unremarkable ability of next-token prediction can change the world, and you will also discover that AI is not as mysterious or as unattainable as imagined. Let's just beat it !

TranslatedCovers pre-training data, Tokenizer, Transformer, MoE,distributed training, Scaling Laws, inference & alignment .6 progressive code assignments for full-stack LLM learning

TranslatedFull-stack learning roadmap and Chinese tutorials for large language models (LLM)🔥: covers Prompt Engineering, RAG, AI Agent, MCP, fine-tuning, model deployment, Transformer, AI programming, and interviews at major tech companies, from beginner level to production practice.

TranslatedA tiny Transformer built from scratch in PyTorch, with an English-to-Chinese translation demo | A small Transformer implemented from scratch with PyTorch, with an English-to-Chinese translation demo, to help understand how the model works