"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.
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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.
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Add this copy of Feature Engineering for Machine Learning: Principles to cart. $57.56, new condition, Sold by Ingram Customer Returns Center rated 5.0 out of 5 stars, ships from NV, USA, published 2018 by O'Reilly Media.
