{"product_id":"9781633439078","title":"Bayesian Optimization in Action","description":"\u003ctable\u003e\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd style=\"\"\u003e\u003cstrong\u003eAuthor\/Contributor(s):\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"\"\u003eNguyen, Quan\u003cbr\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"\"\u003e\u003cstrong\u003ePublisher:\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003eManning\u003cbr\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"\"\u003e\u003cstrong\u003eDate:\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e11\/14\/2023\u003cbr\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"\"\u003e\u003cstrong\u003eBinding:\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"\"\u003ePaperback\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"\"\u003e\u003cstrong\u003eCondition:\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"\"\u003eNEW\u003cbr\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\u003c\/table\u003e\u003cb\u003eBayesian optimization helps pinpoint the best configuration for your machine learning models with speed and accuracy. Put its advanced techniques into practice with this hands-on guide.\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003eIn \u003ci\u003eBayesian Optimization in Action\u003c\/i\u003e you will learn how to:\u003cul\u003e \u003cli\u003eTrain Gaussian processes on both sparse and large data sets\u003c\/li\u003e \u003cli\u003eCombine Gaussian processes with deep neural networks to make them flexible and expressive\u003c\/li\u003e \u003cli\u003eFind the most successful strategies for hyperparameter tuning\u003c\/li\u003e \u003cli\u003eNavigate a search space and identify high-performing regions\u003c\/li\u003e \u003cli\u003eApply Bayesian optimization to cost-constrained, multi-objective, and preference optimization\u003c\/li\u003e \u003cli\u003eImplement Bayesian optimization with PyTorch, GPyTorch, and BoTorch\u003c\/li\u003e \u003c\/ul\u003e\u003cbr\u003e\u003ci\u003eBayesian Optimization in Action\u003c\/i\u003e shows you how to optimize hyperparameter tuning, A\/B testing, and other aspects of the machine learning process by applying cutting-edge Bayesian techniques. Using clear language, illustrations, and concrete examples, this book proves that Bayesian optimization doesn’t have to be difficult! You’ll get in-depth insights into how Bayesian optimization works and learn how to implement it with cutting-edge Python libraries. The book’s easy-to-reuse code samples let you hit the ground running by plugging them straight into your own projects.\u003cbr\u003e\u003cbr\u003eForewords by Luis Serrano and David Sweet\u003ci\u003e.\u003c\/i\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAbout the technology\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003eIn machine learning, optimization is about achieving the best predictions—shortest delivery routes, perfect price points, most accurate recommendations—in the fewest number of steps. Bayesian optimization uses the mathematics of probability to fine-tune ML functions, algorithms, and hyperparameters efficiently when traditional methods are too slow or expensive.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAbout the book\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e\u003ci\u003eBayesian Optimization in Action\u003c\/i\u003e teaches you how to create efficient machine learning processes using a Bayesian approach. In it, you’ll explore practical techniques for training large datasets, hyperparameter tuning, and navigating complex search spaces. This interesting book includes engaging illustrations and fun examples like perfecting coffee sweetness, predicting weather, and even debunking psychic claims. You’ll learn how to navigate multi-objective scenarios, account for decision costs, and tackle pairwise comparisons.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eWhat's inside\u003c\/b\u003e\u003cul\u003e \u003cli\u003eGaussian processes for sparse and large datasets\u003c\/li\u003e \u003cli\u003eStrategies for hyperparameter tuning\u003c\/li\u003e \u003cli\u003eIdentify high-performing regions\u003c\/li\u003e \u003cli\u003eExamples in PyTorch, GPyTorch, and BoTorch\u003c\/li\u003e \u003c\/ul\u003e\u003cbr\u003e\u003cb\u003eAbout the reader\u003c\/b\u003e\u003cbr\u003eFor machine learning practitioners who are confident in math and statistics.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAbout the author\u003c\/b\u003e\u003cbr\u003e\u003cb\u003eQuan Nguyen\u003c\/b\u003e is a research assistant at Washington University in St. Louis. He writes for the Python Software Foundation and has authored several books on Python programming.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e1 Introduction to Bayesian optimization\u003cbr\u003ePART 1 MODELING WITH GAUSSIAN PROCESSES\u003cbr\u003e2 Gaussian processes as distributions over functions\u003cbr\u003e3 Customizing a Gaussian process with the mean and covariance functions\u003cbr\u003ePART 2 MAKING DECISIONS WITH BAYESIAN OPTIMIZATION\u003cbr\u003e4 Refining the best result with improvement-based policies\u003cbr\u003e5 Exploring the search space with bandit-style policies\u003cbr\u003e6 Leveraging information theory with entropy-based policies\u003cbr\u003ePART 3 EXTENDING BAYESIAN OPTIMIZATION TO SPECIALIZED SETTINGS\u003cbr\u003e7 Maximizing throughput with batch optimization\u003cbr\u003e8 Satisfying extra constraints with constrained optimization\u003cbr\u003e9 Balancing utility and cost with multifidelity optimization\u003cbr\u003e10 Learning from pairwise comparisons with preference optimization\u003cbr\u003e11 Optimizing multiple objectives at the same time\u003cbr\u003ePART 4 SPECIAL GAUSSIAN PROCESS MODELS\u003cbr\u003e12 Scaling Gaussian processes to large datasets\u003cbr\u003e13 Combining Gaussian processes with neural networks","brand":"Manning","offers":[{"title":"Default Title","offer_id":44233973793023,"sku":"9781633439078","price":59.99,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0452\/0886\/2873\/files\/Jacket_d402d2a8-dc58-4fae-bd56-fa38398afda0.jpg?v=1771351524","url":"https:\/\/massivebookshop.com\/de\/products\/9781633439078","provider":"MASSIVE BOOKSHOP","version":"1.0","type":"link"}