Automated Machine Learning in Action - Qingquan Song, Haifeng Jin, Xia Hu

Automated Machine Learning in Action

Buch | Softcover
300 Seiten
2022
Manning Publications (Verlag)
978-1-61729-805-9 (ISBN)
64,70 inkl. MwSt
Optimize every stage of your machine learning pipelines with powerful automation components and cutting-edge tools like AutoKeras and KerasTuner. Automated Machine Learning in Action, filled with hands-onexamples and written in an accessible style, reveals how premade machine learning components can automate time-consuming ML tasks.

Automated Machine Learning in Action teaches you to automate selecting the best machine learning models or data preparation methods for your own machine learning tasks, so your pipelines tune themselves without needing constant input. You'll quickly run through machine learning basics thatopen upon AutoML to non-data scientists, before putting AutoML into practicefor image classification, supervised learning, and more.

Automated machine learning (AutoML) automates complex andtime-consuming stages in a machine learning pipeline with pre packaged optimal solutions. This frees up data scientists from data processing and manualtuning, and lets domain experts easily apply machine learning models to their projects.

Qingquan Song, Haifeng Jin, and Dr. Xia “Ben” Hu are the creators of the AutoKeras automated deep learning library. Qingquan and Haifeng are PhD students at Texas A&M University, and have both published papers at major data mining conferences and journals. Dr. Hu is an associate professor at Texas A&M University in the Department of Computer Science and Engineering, whose work has been utilized by TensorFlow, Apple, and Bing.

Erscheinungsdatum
Verlagsort New York
Sprache englisch
Maße 186 x 234 mm
Gewicht 620 g
Themenwelt Mathematik / Informatik Informatik Software Entwicklung
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
ISBN-10 1-61729-805-0 / 1617298050
ISBN-13 978-1-61729-805-9 / 9781617298059
Zustand Neuware
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