it is our pleasure to announce that the book
*Metalearning: Applications to Automated Machine Learning and Data Mining,*
is now Open Access available:
https://link.springer.com/book/10.1007/978-3-030-67024-5
This book offers a comprehensive and thorough introduction to almost all
aspects of metalearning and AutoML, covering the basic concepts and
architecture, evaluation, datasets, hyperparameter optimization, ensembles
and workflows, and also how this knowledge can be used to select, combine,
compose, adapt and configure both algorithms and models to yield faster and
better solutions to data mining and data science problems. It can thus help
developers to develop systems that can improve themselves through
experience.
As one of the fastest-growing areas of research in machine learning,
metalearning studies principled methods to obtain efficient models and
solutions by adapting machine learning and data mining processes. This
adaptation usually exploits information from past experience on other tasks
and the adaptive processes can involve machine learning approaches. As a
related area to metalearning and a hot topic currently, automated machine
learning (AutoML) is concerned with automating the machine learning
processes. Metalearning and AutoML can help AI learn to control the
application of different learning methods and acquire new solutions faster
without unnecessary interventions from the user.
We hope that this book is informative for both you and your students. In
case you have any questions or feedback, don't hesitate to reach out.
Best,
Pavel Brazdil,
Jan N. van Rijn,
Carlos Soares,
Joaquin Vanschoren
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