Explore
Automated Machine Learning
0 Ungluers have
Faved this Work
Login to Fave
This open access book presents the first comprehensive overview of general methods in Automated Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first series of international challenges of AutoML systems. The recent success of commercial ML applications and the rapid growth of the field has created a high demand for off-the-shelf ML methods that can be used easily and without expert knowledge. However, many of the recent machine learning successes crucially rely on human experts, who manually select appropriate ML architectures (deep learning architectures or more traditional ML workflows) and their hyperparameters. To overcome this problem, the field of AutoML targets a progressive automation of machine learning, based on principles from optimization and machine learning itself. This book serves as a point of entry into this quickly-developing field for researchers and advanced students alike, as well as providing a reference for practitioners aiming to use AutoML in their work.
This book is included in DOAB.
Why read this book? Have your say.
You must be logged in to comment.
Rights Information
Are you the author or publisher of this work? If so, you can claim it as yours by registering as an Unglue.it rights holder.Downloads
This work has been downloaded 62 times via unglue.it ebook links.
- 49 - pdf (CC BY) at OAPEN Library.
Keywords
- artificial intelligence
- Computer science
- Computing & information technology
- Image processing
- Optical data processing
- pattern recognition
- thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence
- thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQP Pattern recognition
- thema EDItEUR::U Computing and Information Technology::UY Computer science::UYT Image processing
Links
DOI: 10.1007/978-3-030-05318-5Editions