Bayesian Optimization: Theory and Practice Using Python

Name: Bayesian Optimization: Theory and Practice Using Python
Brand: Apress
SKU: 9781484290620
Price: 4145.0 INR
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by Peng Liu

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ISBN13: 9781484290620
Binding: Paperback
Subject: N/A
Publisher: Apress
Publisher Imprint: Apress
Publication Date: March 24, 2023
Pages: N/A
Original Price: USD 59.99
Language: English
Edition: N/A
Item Weight: 445 grams
BISAC Subject(s): Artificial Intelligence / General and Languages / Python

About The Book

From the Back Cover

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. This book intends to bridge the gap between researchers and practitioners, providing both with a comprehensive, easy-to-digest, and useful reference guide.

After completing this book, you will have a firm grasp of Bayesian optimization techniques, which you'll be able to put into practice in your own machine learning models.

You will:

Apply Bayesian Optimization to build better machine learning models
Understand and research existing and new Bayesian Optimization techniques
Leverage high-performance libraries such as BoTorch, which offer you the ability to dig into and edit the inner working
Dig into the inner workings of common optimization algorithms used to guide the search process in Bayesian optimization

About The Author

Peng Liu is an assistant professor of quantitative finance (practice) at Singapore Management University and an adjunct researcher at the National University of Singapore. He holds a Ph.D. in statistics from the National University of Singapore and has ten years of working experience as a data scientist across the banking, technology, and hospitality industries

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