Model-Based Machine Learning

A fundamental challenge when using machine learning is connecting the abstract mathematics of a machine learning technique to real world problems. This book tackles this challenge through model-based machine learning, focusing on understanding the assumptions encoded in a machine learning system.

List of contents

Introduction. How Can Machine Learning Solve my Problem? 1. A Murder Mystery 2. Assessing People’s Skills Interlude. The Machine Learning Life Cycle 3. Meeting Your Match 4. Uncluttering Your Inbox 5. Making Recommendations 6. Understanding Asthma 7. Harnessing the Crowd 8. How to Read a Model Afterword

About the author

John Winn is a Principal Researcher at Microsoft Research, UK.

Summary

A fundamental challenge when using machine learning is connecting the abstract mathematics of a machine learning technique to real world problems. This book tackles this challenge through model-based machine learning, focusing on understanding the assumptions encoded in a machine learning system.

Product details

• Authors: John Winn, John (Microsoft Research Ltd. Winn
• Publisher: Taylor & Francis Ltd.
• Languages: English
• Product format: Hardback
• Released: 26.10.2023
• EAN: 9781498756815
• ISBN: 978-1-4987-5681-5
• No. of pages: 455
• Subjects: Natural sciences, medicine, IT, technology > Technology > Electronics, electrical engineering, communications engineering; Social sciences, law, business > Business > Miscellaneous; machine learning, BUSINESS & ECONOMICS / Statistics, MATHEMATICS / Probability & Statistics / General, COMPUTERS / Machine Theory, Probability & statistics, Mathematical theory of computation, Automatic control engineering, Probability and statistics, Econometrics and economic statistics