Machine Learning Systems is an open educational repository that serves as the source and learning stack for the Machine Learning Systems textbook, a project focused on teaching how to engineer AI systems that work reliably in real-world environments. Rather than concentrating only on model training, the material emphasizes the broader discipline of AI engineering, covering efficiency, reliability, deployment, and evaluation across the full lifecycle of intelligent systems. The repository includes textbook content, supporting labs, and companion tools such as TinyTorch to help learners move from theory to hands-on experimentation. Its mission is to establish AI systems engineering as a foundational discipline alongside traditional software and computer engineering. The project is structured to guide users through reading, building, and deploying workflows, including running labs on edge devices like Arduino and Raspberry Pi.

Features

  • Open textbook for machine learning systems engineering
  • Integrated TinyTorch hands-on framework
  • Hardware lab pathways for edge deployment
  • Structured learning stack from theory to practice
  • Support for cloud, embedded, and mobile ML workflows
  • Continuously updated open educational content

Project Samples

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Categories

Machine Learning

License

MIT License

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Additional Project Details

Programming Language

JavaScript

Related Categories

JavaScript Machine Learning Software

Registered

2026-02-19