# Machine Learning Systems

> Source: <https://mlsysbook.ai/>
> Published: 2026-06-15 18:14:15+00:00

# Machine Learning Systems

TWO-VOLUME TEXTBOOK

# Machine Learning

Systems.

The physics of AI engineering.

A rigorous, principles-first treatment of how ML systems are built, optimized, and deployed — from a single machine to fleet-scale infrastructure.

Harvard University · MIT Press 2026

Actively maintained
Last updated April 2026
[Release notes](https://github.com/harvard-edge/cs249r_book/releases)

## A complete curriculum for AI engineering.

Choose a path: read the books, explore trade-offs in labs, build the internals with TinyTorch, model constraints with MLSys·im, deploy on real hardware, practice with StaffML, or adopt the full course with the Blueprint.

For Students & Learners

[
](labs/)

EXPLORE

### Labs

Interactive Marimo notebooks. Change a parameter, see what breaks, build intuition.

[
](tinytorch/)

BUILD

### TinyTorch

Build your own ML framework from scratch across 20 progressive modules. Zero magic.

[
](mlsysim/)

MODEL

### MLSys·im

First-principles performance modeling. One command, every bottleneck.

[
](kits/)

DEPLOY

### Hardware Kits

Deploy ML to Arduino, Seeed, Grove, and Raspberry Pi. Real memory limits, real power budgets.

For Career & Instructors

[
](staffml/)

PRACTICE

### StaffML

Physics-grounded interview questions for ML systems roles. Vault, drills, and mock interviews.

[
](instructors/)

ADOPT

### Instructor Hub

The AI Engineering Blueprint: two-semester syllabi, pedagogy guide, rubrics, and TA handbook.

[
](slides/)

TEACH

### Lecture Slides

35 Beamer decks with speaker notes and 266 original SVG diagrams. Drop in and teach.

[
](newsletter/)

FOLLOW

### Newsletter

Updates on the curriculum, new chapters, and what the community is building.

OUR MISSION

AI education should be

free and open to everyone.

Everyone calls AI the new electricity — but electricity is useless without engineers who can build the grid. For AI to be efficient, reliable, and safe, the world needs engineers who understand how to build it.

That knowledge should be accessible to anyone willing to learn. This curriculum is our commitment to making it so.

23,000+ stars · 243,000+ readers · 180+ countries

Our goal: **1,000,000 AI engineers by 2030**

Next milestone: 100,000 ★ — we're at 23,000+.

Every star helps others discover this resource.