Song, Qingguan <br/><br/>
Automated machine learning in action  

 - New York:  Manning Publications Co.,   2022. 
 - xxii, 312p. 
<br/><br/> Includes index. 
<br/><br/> 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. 
<br/><br/><label>ISBN: </label>9781617298059 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Machine learning<br/>Data augmentation<br/>Automated machine learning 
<br/><br/><label>Dewey Class. No.: </label>006.31 SON  / SON