| Description |
1 online resource (1 volume) : illustrations |
| Note |
Includes index. |
| Summary |
Bayesian Optimization in Action 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. |
| Subject |
Bayesian statistical decision theory.
|
|
Mathematical optimization -- Data processing.
|
|
Machine learning -- Mathematics.
|
|
Gaussian processes -- Data processing.
|
|
Théorie de la décision bayésienne. |
|
Optimisation mathématique -- Informatique. |
|
Apprentissage automatique -- Mathématiques. |
|
Processus gaussiens -- Informatique. |
| Added Author |
Serrano, Luis, writer of foreword.
|
|
Sweet, David, writer of foreword.
|
| Other Form: |
Print version: Nguyen, Quan (Computer engineer). Bayesian optimization in action. Shelter Island : Manning Publications, 2023 9781633439078 (OCoLC)1393180690 |
| ISBN |
9781633439078 (electronic bk.) |
|
1633439070 (electronic bk.) |
|
More Resources