Description: Bayesian Optimization in Action by Quan Nguyen Bayesian Optimization in Action teaches you how to build Bayesian Optimisation systems from the ground up. This book transforms state-of-the-art research into usable techniques you can easily put into practice. With a range of illustrations, and concrete examples, this book proves that Bayesian Optimisation doesnt have to be difficult! FORMAT Hardcover LANGUAGE English CONDITION Brand New Publisher Description Apply advanced techniques for optimising machine learning processes For machine learning practitioners confident in maths and statistics. Bayesian Optimization in Action shows you how to optimise hyperparameter tuning, A/B testing, and other aspects of the machine learning process, by applying cutting-edge Bayesian techniques. Using clear language, Bayesian Optimization helps pinpoint the best configuration for your machine-learning models with speed and accuracy. With a range of illustrations, and concrete examples, this book proves that Bayesian Optimisation doesnt have to be difficult! Key features include: Train Gaussian processes on both sparse and large data setsCombine Gaussian processes with deep neural networks to make them flexible and expressiveFind the most successful strategies for hyperparameter tuningNavigate a search space and identify high-performing regionsApply Bayesian Optimisation to practical use cases such as cost-constrained, multi-objective, and preference optimisationUse PyTorch, GPyTorch, and BoTorch to implement Bayesian optimisation You will get in-depth insights into how Bayesian optimisation works and learn how to implement it with cutting-edge Python libraries. The books easy-to-reuse code samples will let you hit the ground running by plugging them straight into your own projects! About the technology Experimenting in science and engineering can be costly and time-consuming, especially without a reliable way to narrow down your choices. Bayesian Optimisation helps you identify optimal configurations to pursue in a search space. It uses a Gaussian process and machine learning techniques to model an objective function and quantify the uncertainty of predictions. Whether youre tuning machine learning models, recommending products to customers, or engaging in research, Bayesian Optimisation can help you make better decisions faster. Author Biography Quan Nguyen is a Python programmer and machine learning enthusiast. He is interested in solving decision-making problems that involve uncertainty. Quan has authored several books on Python programming and scientific computing. He is currently pursuing a PhD degree in Computer Science at Washington University in St. Louis, where he conducts research on Bayesian methods in machine learning. Details ISBN1633439070 Author Quan Nguyen Language English Year 2023 ISBN-10 1633439070 ISBN-13 9781633439078 Publisher Manning Publications Imprint Manning Publications Format Hardcover Place of Publication New York Country of Publication United States AU Release Date 2023-12-06 NZ Release Date 2023-12-06 UK Release Date 2023-12-06 Audience Professional & Vocational DEWEY 519.6 Pages 424 Publication Date 2023-11-21 US Release Date 2023-11-21 We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:157544914;
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Format: Hardcover
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ISBN-13: 9781633439078
Author: Quan Nguyen
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Book Title: Bayesian Optimization in Action
