Automated Machine Learning in Action

Automated Machine Learning in Action

Qingquan Song, Haifeng Jin, Xia Hu
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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 reveals how you can automate the burdensome elements of designing and tuning your machine learning systems. It’s written in a math-lite and accessible style, and filled with hands-on examples for applying AutoML techniques to every stage of a pipeline. AutoML can even be implemented by machine learning novices! If you’re new to ML, you’ll appreciate how the book primes you on machine learning basics. Experienced practitioners will love learning how automated tools like AutoKeras and KerasTuner can create pipelines that automatically select the best approach for your task, or tune any customized search space with user-defined hyperparameters, which removes the burden of manual tuning.
About the technology
Machine learning tasks like data pre-processing, feature selection, and model optimization can be time-consuming and highly technical. Automated machine learning, or AutoML, applies pre-built solutions to these chores, eliminating errors caused by manual processing. By accelerating and standardizing work throughout the ML pipeline, AutoML frees up valuable data scientist time and enables less experienced users to apply machine learning effectively.
About the book
Automated Machine Learning in Action shows you how to save time and get better results using AutoML. As you go, you’ll learn how each component of an ML pipeline can be automated with AutoKeras and KerasTuner. The book is packed with techniques for automating classification, regression, data augmentation, and more. The payoff: Your ML systems will be able to tune themselves with little manual work.
What's inside
• Automatically tune model hyperparameters
• Pick the optimal pipeline components
• Select appropriate models and features
• Learn different search algorithms and acceleration strategies
년:
2022
판:
1
출판사:
Manning Publications / Simon and Schuster
언어:
english
페이지:
336
ISBN 10:
1617298050
ISBN 13:
9781617298059
파일:
EPUB, 9.91 MB
IPFS:
CID , CID Blake2b
english, 2022
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