Python Feature Engineering Cookbook

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Python Feature Engineering Cookbook:
Over 70 recipes for identifying, selecting, and filtering features to build machine learning models
by Soledad Galli

English | 2020 | ISBN: 1789806313 | 364 Pages | PDF,EPUB MOBI | 14 MB
Using Python libraries such as pandas, scikit-learn, Featuretools, and Feature-engine, you'll learn how to work with both continuous and discrete datasets and be able to transform features from unstructured datasets. You will develop the skills necessary to select the best features as well as the most suitable extraction techniques. This book will cover Python recipes that will help you automate feature engineering to simplify complex processes. You'll also get to grips with different feature engineering strategies, such as the box-cox transform, power transform, and log transform across machine learning, reinforcement learning, and natural language processing (NLP) domains.
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