Feature engineering for machine learning : principles and techniques for data scientists

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 featuresthe numeric representations of raw datainto formats for machine-learning models. Each chapter...

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Bibliographic Details
Main Author: Zheng, Alice (Author)
Other Involved Persons: Casari, Amanda
Format: Book
Language:English
Published: Beijing Boston Farnham Sebastopol Tokyo : O'Reilly April 2018
Edition:First edition
ISBN:9781491953242
1491953241
Item Description:Literaturangaben
Revision history for the first edition: 2018-03-23: first release
Physical Description:xiii, 200 Seiten Illustrationen, Diagramme 23,8 x 17,8 cm
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Description:
  • 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 featuresthe numeric representations of raw datainto 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.--
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    ST 302
    ST 304