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