AIE-book covers the entire process from basic models to practical applications, including data preparation, model evaluation, problem solving, etc. The book also provides frameworks for case studies, error analysis, prompt engineering, agent building, fine-tuning models, data validation, model optimization, and continuous improvement. The book is suitable for various technical roles, including AI engineers, data scientists, engineering managers, and product managers.
This GitHub project chiphuyen/aie-book is an open-source book project written by Chip Huyen (Hu Jing), and the title is:
“Introduction to Machine Learning Systems: Design and Implementation”
(Introduction to the Design and Implementation of Machine Learning Systems)
Introduction
This book mainly talks about how to implement machine learning from the research stage to the production environment, which is often referred to as MLOps (Machine Learning Operations) and AI engineering.
Instead of teaching you model algorithms (e.g., CNNs, Transformers), it teaches you:
How to make an AI model truly run in the product, stable, scalable, and maintainable.
Main content structure
According to the catalog content of the warehouse and book, it mainly includes the following parts:
- Overview of machine learning systems
- Why models perform well in the lab but do poorly online
- Differences between ML systems and traditional software engineering
- Build the lifecycle of your AI product
- Data and feature engineering
- Data collection, cleaning, and version management
- Feature extraction and storage
- Data drift and monitoring
- Model training and deployment
- Architecture of offline training and online services
- Model versioning
- Inference performance optimization and latency management
- System Design and Engineering Practice
- How to design a scalable ML system
- How to balance model accuracy with engineering complexity
- Model evaluation metrics vs. A/B testing methodologies
- The whole process of AI products
- Closed-loop feedback from idea → data→ model → service →
- Summary of common pitfalls and experiences in production systems
Author introduction
Chip Huyen:
- Vietnamese-American, graduated from Stanford University with a degree in computer science
- He has worked as an engineer for NVIDIA, Snorkel AI, Netflix, and other companies
- He is currently the co-founder of Claypot AI
- Extensive experience in machine learning system design and real-time ML direction
Her writing style leans towards engineering practice + structured thinking, and this book is called by many Silicon Valley engineers:
“A bridge book that turns researchers into engineers”.
ADDITIONAL INFORMATION
- The repository contains LaTeX source files and code samples for some chapters ;
- The full book has been published by O’Reilly (ISBN 9781098107963 in English);
- A draft of the open-source version is available on GitHub for study and reference.
Github：https://github.com/chiphuyen/aie-book
Tubing: