Bayesian optimization: Theory and practice with Python
This book covers the essential theory and implementation of popular Bayesian optimization techniques in an intuitive and well-illustrated manner. The techniques covered in this book will enable you to better tune the hyperparemeters of your machine learning models and learn sample-efficient approach...
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| Format: | text |
| Language: | English |
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Institutional Knowledge at Singapore Management University
2023
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| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/lkcsb_research/7201 |
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| Institution: | Singapore Management University |
| Language: | English |
| Summary: | This book covers the essential theory and implementation of popular Bayesian optimization techniques in an intuitive and well-illustrated manner. The techniques covered in this book will enable you to better tune the hyperparemeters of your machine learning models and learn sample-efficient approaches to global optimization. The book begins by introducing different Bayesian Optimization (BO) techniques, covering both commonly used tools and advanced topics. It follows a “develop from scratch” method using Python, and gradually builds up to more advanced libraries such as BoTorch, an open-source project introduced by Facebook recently. Along the way, you’ll see practical implementations of this important discipline along with thorough coverage and straightforward explanations of essential theories. |
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