This is a good collection of papers that very neatly outlines challenges and state-of-the art in AutoML! I really liked the coverage on Hyperparameter Optimization.
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Bietet einen guten Überblick und leichten Einstieg in AutoML
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A great resource for a very academic but thorough look at the math, systems, and algorithms tackling the problem of AutoML. It is essentially a collection of papers, which is both good and bad depending on the audience. For instance, if you are looking for a resource to show you how to implement AutoML in your business or to solve a particular problem, then look elsewhere. You will find no tutorials here. However, if you are looking for a look at the various methods and ensembles out there with the full zeal of academic rigor, then start here. I have implemented AutoML before reading this book to toy problems, but I never felt like I grasped what the different algorithms were doing (or how) until I read some of these chapters. It will definitely be a resource I come back to again and again, if not for the content itself, then for the vast trove of references. Recommended (to the right audience).
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Ganz nett
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für mich allerdings doch zu starker Tobak :) Geht sehr in die Tiefe und setzt viel Wissen voraus
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