Evaluating and Fine-Tuning Regression Models in Python with Scikit-learn

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AutoML: Methods, Systems, Challenges

Description

The books in this innovative series collect papers written in the context of successful competitions in machine learning. They also include analyses of the challenges, tutorial material, dataset descriptions, and pointers to data and software. Together with the websites of the challenge competitions, they offer a complete teaching toolkit and a valuable resource for engineers and scientists.

By Frank Hutter, Lars Kotthoff, and Joaquin VanschorenRead more.

Career Relevance by Data Role

The techniques and tools covered in AutoML: Methods, Systems, Challenges are most similar to the requirements found in Data Scientist job advertisements.

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