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HTTP/2 301 server: GitHub.com content-type: text/html location: https://openmlsys.github.io/html-en/ x-github-request-id: 0D79:2C10E1:9ADDD9:ADEFC5:69536493 accept-ranges: bytes age: 0 date: Tue, 30 Dec 2025 05:35:20 GMT via: 1.1 varnish x-served-by: cache-bom-vanm7210033-BOM x-cache: MISS x-cache-hits: 0 x-timer: S1767072920.885262,VS0,VE196 vary: Accept-Encoding x-fastly-request-id: 34c8c98ef232520d83a26b228c86099227c43e28 content-length: 162 HTTP/2 200 server: GitHub.com content-type: text/html; charset=utf-8 last-modified: Thu, 27 Mar 2025 22:27:58 GMT access-control-allow-origin: * strict-transport-security: max-age=31556952 etag: W/"67e5d0ee-dae5" expires: Tue, 30 Dec 2025 05:45:20 GMT cache-control: max-age=600 content-encoding: gzip x-proxy-cache: MISS x-github-request-id: 1EEC:1387E:997519:AC870E:69536495 accept-ranges: bytes age: 0 date: Tue, 30 Dec 2025 05:35:20 GMT via: 1.1 varnish x-served-by: cache-bom-vanm7210033-BOM x-cache: MISS x-cache-hits: 0 x-timer: S1767072920.095333,VS0,VE218 vary: Accept-Encoding x-fastly-request-id: 49349daefa7ad1b4d1f545b7ad50391f83d4e5ae content-length: 6422 Machine Learning Systems: Design and Implementation — Machine Learning Systems: Design and Implementation 1.0.0 documentation

Machine Learning Systems: Design and Implementation

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GitHub 中文版

Table Of Contents

1. Preface
2. Introduction
3. Part I Framework Design
4. Programming Model
5. AI Compiler Frontend
6. AI Compiler Backend
7. Hardware Accelerator
8. Distributed Training
9. Model Deployment
10. Part II Application Scenarios
11. Recommender System
12. Reinforcement Learning System
13. Robotic System

Table Of Contents

1. Preface
2. Introduction
3. Part I Framework Design
4. Programming Model
5. AI Compiler Frontend
6. AI Compiler Backend
7. Hardware Accelerator
8. Distributed Training
9. Model Deployment
10. Part II Application Scenarios
11. Recommender System
12. Reinforcement Learning System
13. Robotic System

Machine Learning Systems: Design and Implementation¶

《Machine Learning Systems: Design and Implementation》

Coming Soon!

Be the world's first open source book that comprehensively introduces the knowledge of machine learning systems

Core Author

Luo Mai

University of Edinburgh

Hao Dong

Peking University, Peng Cheng Laboratory

Xuefeng Jin

MindSpore Architect

Zhiliang Gan

MindSpore Architect

Chapter Author

Cheng Lai

Peng Cheng Laboratory

Jiarong Han

Peng Cheng Laboratory

Yao Fu

University of Edinburgh

Xiulong Yuan

Tsinghua University

Zihan Ding

Princeton University

Jiankai Sun

Stanford University

Peiyuan Liao

Carnegie Mellon University

Wenteng Liang

Beijing University of Posts and Telecommunications

Jie Ren

University of Edinburgh

Hanchen Wang

University of Cambridge

Pei Mu

University of Edinburgh

Qinghua Zhang

Huawei Engineer

Zhibo Liang

Huawei Engineer

Jianfeng Yu

Huawei Engineer

Jinjin Chu

Huawei Engineer

Fubi Cai

Huawei Engineer

Renwei Zhang

Huawei Engineer

Chao Liu

Huawei Engineer

Gang Chen

Huawei Engineer

Mingqi Li

Huawei Engineer

Gangqiang Han

Huawei Engineer

Yehui Tang

Huawei Engineer

Zhiqiang Zhai

Huawei Engineer

Tiancheng Wu

Huawei Engineer

Xiaohui Li

Huawei Engineer

Haoyang Li

Huawei Engineer

Zhipeng Tan

Huawei Engineer

Shanni Li

Huawei Engineer

Zhijian Guo

Huawei Engineer

Thanks to contributors from the community

Thanks to readers who provided valuable comments for this book

Contributions to this book are welcome

Table of contents

1. Preface
2. Introduction
3. Part I Framework Design
4. Programming Model
5. AI Compiler Frontend
6. AI Compiler Backend
7. Hardware Accelerator
8. Distributed Training
9. Model Deployment
10. Part II Application Scenarios
11. Recommender System
12. Reinforcement Learning System
13. Robotic System

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