Category:    Programming     Hyperparameter Optimization in Machine Learning: Make Your Machine Learning and Deep Learning Models More Efficient free ebook download

Views:  149 Likes:  4 Catalogue

Author(s): Tanay Agrawal Date: 2020-11-29 Format: PDF Language: English ISBN/ASIN: 1484265785 Pages: 166 OCR: Quality: ISBN13: Uploader: topron Upload Date: 1/13/2021 9:46:22 AM     To download click on link in the Links Table below                                                                        Description: Click to see full description Dive into hyperparameter tuning of machine learning models and focus on what hyperparameters are and how they work. This book discusses different techniques of hyperparameters tuning, from the basics to advanced methods. This is a step-by-step guide to hyperparameter optimization, starting with what hyperparameters are and how they affect different aspects of machine learning models. It then goes through some basic (brute force) algorithms of hyperparameter optimization. Further, the author addresses the problem of time and memory constraints, using distributed optimization methods. Next youll discuss Bayesian optimization for hyperparameter search, which learns from its previous history. The book discusses different frameworks, such as Hyperopt and Optuna, which implements sequential model-based global optimization (SMBO) algorithms. During these discussions, youll focus on different aspects such as creation of search spaces and distributed optimization of these libraries. Hyperparameter Optimization in Machine Learning creates an understanding of how these algorithms work and how you can use them in real-life data science problems. The final chapter summaries the role of hyperparameter optimization in automated machine learning and ends with a tutorial to create your own AutoML script. Hyperparameter optimization is tedious task, so sit back and let these algorithms do your work. What You Will Learn Discover how changes in hyperparameters affect the models performance. Apply different hyperparameter tuning algorithms to data science problems Work with Bayesian optimization methods to create efficient machine learning and deep learning models Distribute hyperparameter optimization using a cluster of machines Approach automated machine learning using hyperparameter optimization Who This Book Is For Professionals and students working with machine learning. Links Table     Title Link Password Size (MB) Thank to Inform Admin Del 2938352 Book https://nitroflare.com/view/FE35E548783F...   6.40 topron X Title Link Password Size Reason Dead link New format   Those who downloaded this book also downloaded the following books: Comments New comment:

(C) FreeBookSpot 2007 - 2018