Introduction to Machine Learning Systems

A comprehensive guide to designing and building production-ready machine learning systems. This Harvard CS249r course book covers essential concepts in ML system architecture, deployment strategies, scalability, and best practices for taking machine learning models from research to production across edge, mobile, and cloud platforms.

Dr. Vijay Janappa Reddy provides practical insights into the challenges of building robust ML systems, including data pipelines, model serving, monitoring, and maintenance. This open-source textbook is an invaluable resource for aspiring ML engineers and PhD students interested in the systems aspects of machine learning, from TinyML to cloud-scale deployments.

Resources:

• 📚 Online Book: mlsysbook.ai
• 💻 GitHub Repository: harvard-edge/cs249r_book
• ⭐ 8.8k+ stars on GitHub with contributions from 91+ contributors worldwide