A pre-publication version of the foundational content is often available on arXiv . Deep Review: Key Takeaways
It details the series, which evaluates how well these automated systems perform against human experts on "blind" datasets. Critical Reception
The book is structured into three main parts: , Systems , and Challenges . 1. Methods (The "How") Download Book Automated Machine Learning pdf
A robust system based on the popular scikit-learn library that uses meta-learning to warm-start optimization. 3. Challenges (The Evaluation)
This section covers the core algorithms that power automation. A pre-publication version of the foundational content is
Because it is a collection of academic papers, it lacks a cohesive tutorial-style narrative; there are no step-by-step business implementation guides. Frank Hutter Lars Kotthoff Joaquin Vanschoren Editors
The publisher provides the complete book PDF and individual chapters for free. Challenges (The Evaluation) This section covers the core
One of the first systems to simultaneously select algorithms and hyperparameters.