Lecture Slides
35 Beamer decks, TinyML courseware, speaker notes, active learning, and 266 original SVG diagrams. Free to download, customize, and teach from.
Vol I · Ch 1: Title Slide — Custom Beamer Theme
Vol I · Ch 1: The Iron Law — Focus Slides for Key Equations
Vol I · Ch 11: The Roofline Model — Original SVG Diagrams
Vol II · Ch 2: Three Walls — Quantitative Systems Tables
Vol II · Ch 3: RDMA & GPUDirect — Semantic Color Diagrams
Vol II · Ch 7: Optimal Checkpointing — Math + Visualization
Vol I · Ch 1: The Degradation Equation — Every Slide Has Speaker Notes
Preview of Beamer slides (Vol I & II) — 7 of 1,099 shown. Every slide includes speaker notes and timing guidance.
Introduction to Machine Learning Systems
17 decks covering the full single-machine ML stack: data engineering, neural computation, architectures, frameworks, training, compression, hardware, serving, and operations.
Volume IIMachine Learning Systems at Scale
18 decks covering distributed infrastructure: compute clusters, network fabrics, distributed training, fault tolerance, fleet orchestration, inference at scale, and governance.
TinyMLTiny Machine Learning
Complete edX courseware: ML fundamentals, keyword spotting, visual wake words, anomaly detection, embedded deployment on Arduino, and MLOps at scale.
| Speaker Notes | Every slide has timing estimates, teaching guidance, common student errors, and discussion prompts. | Guide → |
| Active Learning | 5+ exercises per deck: predict, calculate, discuss, peer instruction, retrieval practice, muddiest point. | Details → |
| SVG Diagrams | 266 original vector diagrams with semantic colors. Editable source files — not locked images. | Source → |
| PowerPoint | Every deck available as PPTX for presenter mode and annotations. Image-based (not editable). | Download → |
| Beamer Source | Full LaTeX source with custom theme. Fork, customize, rebuild with make. |
Customize → |
| Semester Plans | 16-week schedules for Vol I, Vol II, a combined 32-week plan, and a 10–12 week TinyML syllabus. | Plans → |
| Textbook | The slides are derived from this two-volume open textbook. Read online or download PDF. | Vol I · Vol II |
| Instructor Blueprint | Syllabi, assessment rubrics, TA guide, and course customization — the full teaching toolkit. | Blueprint → |
| Interactive Labs | 32 browser-based labs powered by MLSys·IM. Pair with slides for hands-on learning. | Labs → |
| Hardware Kits | Arduino, Raspberry Pi, and Seeed deployment labs for TinyML and edge AI. | Kits → |