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Python Feature Engineering Cookbook by Galli Soledad (35 results)
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Python Feature Engineering Cookbook - Third Edition: A complete guide to crafting powerful features for your machine learning models (Paperback or Softback)
Published by Packt Publishing 8/30/2024, 2024
ISBN 10: 1835883583 ISBN 13: 9781835883587
Language: English
Paperback or Softback. Condition: New. Python Feature Engineering Cookbook - Third Edition: A complete guide to crafting powerful features for your machine learning models 1.49. Book.
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Python Feature Engineering Cookbook - Second Edition: Over 70 recipes for creating, engineering, and transforming features to build machine learning m (Paperback or Softback)
Published by Packt Publishing 10/31/2022, 2022
ISBN 10: 1804611301 ISBN 13: 9781804611302
Language: English
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Python Feature Engineering Cookbook: A complete guide to crafting powerful features for your machine learning models
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Python Feature Engineering Cookbook - Third Edition: A complete guide to crafting powerful features for your 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, 2nd Edition
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Python Feature Engineering Cookbook - Third Edition: A complete guide to crafting powerful features for your machine learning models
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Python Feature Engineering Cookbook
Published by Packt Publishing (edition ), 2020
ISBN 10: 1789806313 ISBN 13: 9781789806311
Language: English
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Python Feature Engineering Cookbook (Paperback or Softback)
Published by Packt Publishing 1/22/2020, 2020
ISBN 10: 1789806313 ISBN 13: 9781789806311
Language: English
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Python Feature Engineering Cookbook
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Python Feature Engineering Cookbook
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Python Feature Engineering Cookbook
Published by Packt Publishing, Limited, 2022
ISBN 10: 1804611301 ISBN 13: 9781804611302
Language: English
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Python Feature Engineering Cookbook: A complete guide to crafting powerful features for your machine learning models
Published by Packt Publishing Limited, 2024
ISBN 10: 1835883583 ISBN 13: 9781835883587
Language: English
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Python Feature Engineering Cookbook -: Over 70 recipes for creating, engineering, and transforming features to build machine learning models
Published by Packt Publishing Limited, 2022
ISBN 10: 1804611301 ISBN 13: 9781804611302
Language: English
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
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Add to basketTaschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Leverage the power of Python to build real-world feature engineering and machine learning pipelines ready to be deployed to productionKey Features: Craft powerful features from tabular, transactional, and time-series data Develop efficient and reproducible real-world feature engineering pipelines Optimize data transformation and save valuable time Purchase of the print or Kindle book includes a free PDF Elektronisches BuchBook Description:Streamline data preprocessing and feature engineering in your machine learning project with this third edition of the Python Feature Engineering Cookbook to make your data preparation more efficient.This guide addresses common challenges, such as imputing missing values and encoding categorical variables using practical solutions and open source Python libraries.You'll learn advanced techniques for transforming numerical variables, discretizing variables, and dealing with outliers. Each chapter offers step-by-step instructions and real-world examples, helping you understand when and how to apply various transformations for well-prepared data.The book explores feature extraction from complex data types such as dates, times, and text. You'll see how to create new features through mathematical operations and decision trees and use advanced tools like Featuretools and tsfresh to extract features from relational data and time series.By the end, you'll be ready to build reproducible feature engineering pipelines that can be easily deployed into production, optimizing data preprocessing workflows and enhancing machine learning model performance.What You Will Learn: Discover multiple methods to impute missing data effectively Encode categorical variables while tackling high cardinality Find out how to properly transform, discretize, and scale your variables Automate feature extraction from date and time data Combine variables strategically to create new and powerful features Extract features from transactional data and time series Learn methods to extract meaningful features from text dataWho this book is for:If you're a machine learning or data science enthusiast who wants to learn more about feature engineering, data preprocessing, and how to optimize these tasks, this book is for you. If you already know the basics of feature engineering and are looking to learn more advanced methods to craft powerful features, this book will help you. You should have basic knowledge of Python programming and machine learning to get started.Table of Contents Imputing Missing Data Encoding Categorical Variables Transforming Numerical Variables Performing Variable Discretization Working with Outliers Extracting Features from Date and Time Variables Performing Feature Scaling Creating New Features Extracting Features from Relational Data with Featuretools Creating Features from a Time Series with tsfresh Extracting Features from Text Variables.
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US$ 58.02
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Add to basketCondition: New. Feature engineering is invaluable for developing and enriching your machine learning models. In this book, you will work with the best Python tools to streamline your feature engineering pipelines, feature engineering techniques and simplify and improve the.
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Add to basketTaschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Create end-to-end, reproducible feature engineering pipelines that can be deployed into production using open-source Python librariesKey Features:Learn and implement feature engineering best practicesReinforce your learning with the help of multiple hands-on recipesBuild end-to-end feature engineering pipelines that are performant and reproducibleBook Description:Feature engineering, the process of transforming variables and creating features, albeit time-consuming, ensures that your machine learning models perform seamlessly. This second edition of Python Feature Engineering Cookbook will take the struggle out of feature engineering by showing you how to use open source Python libraries to accelerate the process via a plethora of practical, hands-on recipes.This updated edition begins by addressing fundamental data challenges such as missing data and categorical values, before moving on to strategies for dealing with skewed distributions and outliers. The concluding chapters show you how to develop new features from various types of data, including text, time series, and relational databases. With the help of numerous open source Python libraries, you'll learn how to implement each feature engineering method in a performant, reproducible, and elegant manner.By the end of this Python book, you will have the tools and expertise needed to confidently build end-to-end and reproducible feature engineering pipelines that can be deployed into production.What You Will Learn:Impute missing data using various univariate and multivariate methodsEncode categorical variables with one-hot, ordinal, and count encodingHandle highly cardinal categorical variablesTransform, discretize, and scale your variablesCreate variables from date and time with pandas and Feature-engineCombine variables into new featuresExtract features from text as well as from transactional data with FeaturetoolsCreate features from time series data with tsfreshWho this book is for:This book is for machine learning and data science students and professionals, as well as software engineers working on machine learning model deployment, who want to learn more about how to transform their data and create new features to train machine learning models in a better way.
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US$ 93.63
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Add to basketPaperback. Condition: New. New. book.
