Download free course Automated Machine Learning, pdf file on 223 pages by by Frank Hutter, Lars Kotthoff, Joaquin Vanschoren.
This 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.
Table of contents
| Pages : |
223 |
| Size : |
6.4 MB |
| Downloads: |
62 |
| Created: |
2022-02-01 |
| License: |
CC BY |
| Author(s): |
by Frank Hutter, Lars Kotthoff, Joaquin Vanschoren |
Download file
Others related eBooks about Automated Machine Learning
Machine Learning for Cyber Physical Systems
This Open Access proceedings presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains some selected papers from the international Conference ML4CPS – Machine Learning for Cyber Physical Systems, which was held in Karlsruhe, October 23-24, 2018.
Download free course Python Machine Learning Projects, pdf file on 135 pages by Lisa Tagliaferri, Michelle Morales, Ellie Birkbeck, Alvin Wan.
Machine learning techniques provide cost-effective alternatives to traditional methods for extracting underlying relationships between information and data and for predicting future events by processing existing information to train models. Efficient Learning Machines explores the major topics of ma
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.
Everything you really need to know in Machine Learning in a hundred pages!