Optimize every stage of your machine learning pipelines with powerful automation components and cutting-edge tools like AutoKeras and Keras Tuner.
Automating automation itself is a new concept and this book does justice to it in terms of explaining the concepts, sharing real world advancements, use cases and research related to the topic.
In Automated Machine Learning in Action
you will learn how to:
Automated Machine Learning in Action
- Improve a machine learning model by automatically tuning its hyperparameters
- Pick the optimal components for creating and improving your pipelines
- Use AutoML toolkits such as AutoKeras and Keras Tuner
- Design and implement search algorithms to find the best component for your ML task
- Accelerate the AutoML process with data-parallel, model pretraining, and other techniques
reveals how premade machine learning components can automate time-consuming ML tasks. 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. You’ll use tools like AutoKeras to create pipelines that automatically select the best approach for your task, remove the burden of manual tuning, and can even be implemented by machine learning novices!