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Feature Engineering for Machine Learning
By:Alice Zheng,Amanda Casari
Published on 2018-03-23 by |O'Reilly Media, Inc.|

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. Rather than simply teach these principles, authors Alice Zheng and Amanda Casari focus on practical application with exercises throughout the book. The closing chapter brings everything together by tackling a real-world, structured dataset with several feature-engineering techniques. Python packages including numpy, Pandas, Scikit-learn, and Matplotlib are used in code examples. You’ll examine: Feature engineering for numeric data: filtering, binning, scaling, log transforms, and power transforms Natural text techniques: bag-of-words, n-grams, and phrase detection Frequency-based filtering and feature scaling for eliminating uninformative features Encoding techniques of categorical variables, including feature hashing and bin-counting Model-based feature engineering with principal component analysis The concept of model stacking, using k-means as a featurization technique Image feature extraction with manual and deep-learning techniques

This Book was ranked at 32 by Google Books for keyword engineering books.

Book ID of Feature Engineering for Machine Learning's Books is sthSDwAAQBAJ, Book which was written byAlice Zheng,Amanda Casarihave ETAG "wElLeUfGQrg"

Book which was published by |O'Reilly Media, Inc.| since 2018-03-23 have ISBNs, ISBN 13 Code is 9781491953198 and ISBN 10 Code is 1491953195

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