|
Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
|
Buy Now
Hyperparameter Optimization in Machine Learning - Make Your Machine Learning and Deep Learning Models More Efficient (Paperback, 1st ed.)
Loot Price: R1,090
Discovery Miles 10 900
You Save: R303
(22%)
|
|
|
Hyperparameter Optimization in Machine Learning - Make Your Machine Learning and Deep Learning Models More Efficient (Paperback, 1st ed.)
Expected to ship within 10 - 15 working days
|
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 you'll 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, you'll 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
model's 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.
General
Is the information for this product incomplete, wrong or inappropriate?
Let us know about it.
Does this product have an incorrect or missing image?
Send us a new image.
Is this product missing categories?
Add more categories.
Review This Product
No reviews yet - be the first to create one!
|
|
Email address subscribed successfully.
A activation email has been sent to you.
Please click the link in that email to activate your subscription.
Welcome to Loot.co.za!
Sign in / Register |Wishlists & Gift Vouchers |Help | Advanced search
