Supervised Machine Learning for Science
How to stop worrying and love your black box
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Supervised Machine Learning for Science
How to stop worrying and love your black box
About this book
Machine learning has revolutionized science, from folding proteins and predicting tornadoes to studying human nature. While science has always had an intimate relationship with prediction, machine learning amplified this focus. But can this hyper-focus on prediction be justified? Can a machine learning model be part of a scientific model? Or are we on the wrong track?
In this book, we explore and justify supervised machine learning in science. However, a naive application of supervised learning won't get you far because machine learning in raw form is unsuitable for science. After all, it lacks interpretability, causality, uncertainty quantification, and many more desirable attributes. Yet, we already have all the puzzle pieces needed to improve machine learning, from incorporating domain knowledge to creating robust, interpretable, and causal models. The problem is that the solutions are scattered everywhere.
In this book, we bring together the philosophical justification and the solutions that make supervised machine learning a powerful tool for science.
The book consists of two parts:
Part 1 justifies the use of machine learning in science.
Part 2 discusses how to integrate machine learning into science.
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Information
Table of contents
- Supervised Machine Learning for Science
- Summary
- Preface
- 1 Introduction
- 2 Bare-Bones Supervised Machine Learning
- 3 The Role of Prediction in Science
- 4 Justification to Use Machine Learning
- 5 Machine Learning and Other Scientific Goals: A Clash
- 6 Bare-Bones Machine Learning is Insufficient
- 7 Generalization
- 8 Domain Knowledge
- 9 Interpretability
- 10 Causality
- 11 Robustness
- 12 Uncertainty
- 13 Reproducibility
- 14 Reporting
- 15 The Future of Science in the Age of Machine Learning
- Acknowledgments
- Citing this Book
- About the Authors
- References
- Impressum