Zheng, Alice <br/><br/>
Feature engineering for machine learning: principles and techniques for data scientists 

 - Sebastopol:  O'Reilly Media,  2018. 
 - xiii, 200p.;  pbk;  23cm. 
<br/><br/>Includes index. 
<br/><br/> Feature engineering is a crucial step in the machine-learning pipeline, yet this topic is rarely examined on its own. With this practical book, you’ll learn techniques for extracting and transforming features—the numeric representations of raw data—into formats for machine-learning models. Each chapter guides you through a single data problem, such as how to represent text or image data. Together, these examples illustrate the main principles of feature engineering.<br/><br/>https://www.oreilly.com/library/view/feature-engineering-for/9781491953235/ 
<br/><br/><label>ISBN: </label>9789352137114 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Machine learning<br/>Data mining<br/>Engineering<br/>K-mean model<br/>Image fearture extraction
<br/><br/><label>Dewey Class. No.: </label>006.31  / ZHE