Volume 1 · 20 chapters
Classical Data Science
The foundations. Framing the business problem, the maths, Python and SQL. Then the classical ML toolkit: ensembles, validation, features, evaluation and time series.
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书籍Books
Series
A Solutions Architect's Field Guide
A field guide for solutions architects moving into data science and AI. Four volumes, 83 chapters, from statistics to world models. Every chapter pairs the ideas with trade-offs, a worked example and code you can run.
Volume 2 · 17 chapters
Modern AI
From MLOps to LLMs. Responsible AI, deployment and monitoring. Then neural networks, transformers, RAG, fine-tuning, RLHF and agents.
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Volume 3 · 20 chapters
Systems & Performance
Making it fast. GPU architecture, CUDA and Triton kernels. Then CPU performance: profiling, SIMD, parallelism and memory. Ends with an end-to-end optimization.
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Volume 4 · 26 chapters
Applied AI Domains
Three frontiers. Physical AI: perception, world models, VLAs and robot policies. Image models, from CNNs to diffusion. Knowledge graphs, GraphRAG and agentic reasoning.
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