Description: Bayesian Optimization : Theory and Practice Using Python, Paperback by Liu, Peng, ISBN 1484290623, ISBN-13 9781484290620, Brand New, Free shipping in the US 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.Th 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 Fac 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. What You Will LearnApply Bayesian Optimization to build better machine learning modelsUnderstand and research existing and new Bayesian Optimization techniquesLeverage high-performance libraries such as BoTorch, which offer you the ability to dig into and edit the inner workingDig into the inner workings of common optimization algorithms used to guide the search process in Bayesian optimization Who This Book Is ForBeginner to intermediate level professionals in machine learning, analytics or other roles relevant in data science.
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Book Title: Bayesian Optimization : Theory and Practice Using Python
Number of Pages: Xv, 234 Pages
Publication Name: Bayesian Optimization : Theory and Practice Using Python
Language: English
Publisher: Apress L. P.
Subject: Intelligence (Ai) & Semantics, Probability & Statistics / General, General, Programming Languages / Python
Publication Year: 2023
Item Weight: 17.1 Oz
Type: Textbook
Subject Area: Mathematics, Computers
Item Length: 10 in
Author: Peng Liu
Item Width: 7 in
Format: Trade Paperback
