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- Python Feature Engineering Cookbook. Over 70 recipes for creating, engineering, and transforming features to build machine learning models
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Python Feature Engineering Cookbook. Over 70 recipes for creating, engineering, and transforming features to build machine learning models
Ebook
Feature engineering is invaluable for developing and enriching your machine learning models. In this cookbook, you will work with the best tools to streamline your feature engineering pipelines and techniques and simplify and improve the quality of your code.
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.
By the end of this book, you’ll have discovered tips and practical solutions to all of your feature engineering problems.
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.
By the end of this book, you’ll have discovered tips and practical solutions to all of your feature engineering problems.
- 1. Foreseeing Variable Problems When Building ML Models
- 2. Imputing Missing Data
- 3. Encoding Categorical Variables
- 4. Transforming Numerical Variables
- 5. Performing Variable Discretisation
- 6. Working with Outliers
- 7. Deriving Features from Dates and Time Variables
- 8. Performing Feature Scaling
- 9. Applying Mathematical Computations to Features
- 10. Creating Features with Transactional and Time Series Data
- 11. Extracting Features from Text Variables
- Title: Python Feature Engineering Cookbook. Over 70 recipes for creating, engineering, and transforming features to build machine learning models
- Author: Soledad Galli
- Original title: Python Feature Engineering Cookbook. Over 70 recipes for creating, engineering, and transforming features to build machine learning models
- ISBN: 9781789807820, 9781789807820
- Date of issue: 2020-01-22
- Format: Ebook
- Item ID: e_2aag
- Publisher: Packt Publishing