Feature Engineering for Machine Learning Models
Principles and Techniques for Data Scientists
(Sprache: Englisch)
"Feature engineering is a crucial step in the machine-learning pipeline, yet this topic is rarely examined on its own. With this practical book, youll learn techniques for extracting and transforming features-the numeric representations of raw data-into...
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"Feature engineering is a crucial step in the machine-learning pipeline, yet this topic is rarely examined on its own. With this practical book, youll 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."--Page 4 of cover.
Autoren-Porträt von Alice Zheng, Amanda Casari
Alice is a technical leader in the field of Machine Learning. Her experience spans algorithm and platform development and applications. Currently, she is a Senior Manager in Amazon's Ad Platform. Previous roles include Director of Data Science at GraphLab/Dato/Turi, machine learning researcher at Microsoft Research, Redmond, and postdoctoral fellow at Carnegie Mellon University. She received a Ph.D. in Electrical Engineering and Computer science, and B.A. degrees in Computer Science in Mathematics, all from U.C. Berkeley.
Bibliographische Angaben
- Autoren: Alice Zheng , Amanda Casari
- 2018, XIII, 200 Seiten, Masse: 17,8 x 23,8 cm, Kartoniert (TB), Englisch
- Verlag: O'Reilly Media
- ISBN-10: 1491953241
- ISBN-13: 9781491953242
Sprache:
Englisch
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