harvard-edge/cs249r_book

原文摘要

Machine Learning Systems Machine Learning Systems Principles and Practices of Engineering Artificially Intelligent Systems English • 中文 • 日本語 • 한국어 📘 Textbook • 📗 Vol I + 📘 Vol II • 🔥 TinyTorch • 🔬 Labs • 🔮 MLSys·im • 💼 StaffML 📚 Hardcopy edition coming 2026 with MIT Press. Mission The world is rushing to build AI systems. It is not engineering them. That gap is what we mean by AI engineering. AI engineering is the discipline of building efficient, reliable, safe, and robust intelligent systems that operate in the real world, not just models in isolation. Our mission is to establish AI engineering as a foundational discipline alongside software engineering and computer engineering, by teaching how to design, build, and evaluate end-to-end intelligent systems. Our goal: Help 100,000 learners master ML Systems this year, and reach 1 million by 2030 . Why One Repository I designed this as a single integrated curriculum, not a collection of independent projects. The textbook teaches the theory. TinyTorch makes you build the internals. The hardware kits force you to confront real constraints. The simulator lets you reason about infrastructure you can't afford to rent. Each piece…