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Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
EUR 47,08
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Ajouter au panierEtat : New. In.
Edité par Packt Publishing 8/30/2024, 2024
ISBN 10 : 1835883583 ISBN 13 : 9781835883587
Langue: anglais
Vendeur : BargainBookStores, Grand Rapids, MI, Etats-Unis
EUR 43,13
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Ajouter au panierPaperback or Softback. Etat : New. Python Feature Engineering Cookbook - Third Edition: A complete guide to crafting powerful features for your machine learning models 1.49. Book.
Vendeur : WorldofBooks, Goring-By-Sea, WS, Royaume-Uni
EUR 8,55
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Ajouter au panierPaperback. Etat : Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
EUR 40,81
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Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
EUR 44,53
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Ajouter au panierEtat : As New. Unread book in perfect condition.
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
EUR 47,07
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Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
EUR 51,39
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Ajouter au panierEtat : As New. Unread book in perfect condition.
Edité par Packt Publishing (edition ), 2020
ISBN 10 : 1789806313 ISBN 13 : 9781789806311
Langue: anglais
Vendeur : BooksRun, Philadelphia, PA, Etats-Unis
EUR 15,30
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Ajouter au panierPaperback. Etat : Good. Ship within 24hrs. Satisfaction 100% guaranteed. APO/FPO addresses supported.
Edité par Packt Publishing - ebooks Account -, 2020
ISBN 10 : 1789806313 ISBN 13 : 9781789806311
Langue: anglais
Vendeur : Bahamut Media, Reading, Royaume-Uni
EUR 22,47
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Ajouter au panierpaperback. Etat : Very Good. Shipped within 24 hours from our UK warehouse. Clean, undamaged book with no damage to pages and minimal wear to the cover. Spine still tight, in very good condition. Remember if you are not happy, you are covered by our 100% money back guarantee.
Edité par Packt Publishing - ebooks Account, 2020
ISBN 10 : 1789806313 ISBN 13 : 9781789806311
Langue: anglais
Vendeur : AwesomeBooks, Wallingford, Royaume-Uni
EUR 22,47
Autre deviseQuantité disponible : 1 disponible(s)
Ajouter au panierpaperback. Etat : Very Good. Python Feature Engineering Cookbook: Over 70 recipes for creating, engineering, and transforming features to build machine learning models This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. This book has clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping. .
EUR 17,35
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Ajouter au panierPaperback. Etat : Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less 1.63.
EUR 43,35
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Ajouter au panierEtat : New. In.
EUR 43
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Edité par Packt Publishing 1/22/2020, 2020
ISBN 10 : 1789806313 ISBN 13 : 9781789806311
Langue: anglais
Vendeur : BargainBookStores, Grand Rapids, MI, Etats-Unis
EUR 42,24
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Ajouter au panierPaperback or Softback. Etat : New. Python Feature Engineering Cookbook 1.41. Book.
Vendeur : California Books, Miami, FL, Etats-Unis
EUR 48,27
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Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
EUR 52,06
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Edité par Packt Publishing 10/31/2022, 2022
ISBN 10 : 1804611301 ISBN 13 : 9781804611302
Langue: anglais
Vendeur : BargainBookStores, Grand Rapids, MI, Etats-Unis
EUR 47,55
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Ajouter au panierPaperback or Softback. Etat : New. Python Feature Engineering Cookbook - Second Edition: Over 70 recipes for creating, engineering, and transforming features to build machine learning m 1.46. Book.
EUR 48,76
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Ajouter au panierEtat : 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.
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
EUR 44,24
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Ajouter au panierEtat : New.
Edité par Packt Publishing Limited, GB, 2022
ISBN 10 : 1804611301 ISBN 13 : 9781804611302
Langue: anglais
Vendeur : Rarewaves.com UK, London, Royaume-Uni
EUR 63,12
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Ajouter au panierPaperback. Etat : New. Create end-to-end, reproducible feature engineering pipelines that can be deployed into production using open-source Python librariesKey FeaturesLearn 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 DescriptionFeature 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 learnImpute 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 forThis 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.
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
EUR 49,53
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Ajouter au panierEtat : As New. Unread book in perfect condition.
Edité par Packt Publishing Limited, 2024
ISBN 10 : 1835883583 ISBN 13 : 9781835883587
Langue: anglais
Vendeur : THE SAINT BOOKSTORE, Southport, Royaume-Uni
EUR 51,94
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Ajouter au panierPaperback / softback. Etat : New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 526.
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
EUR 52,05
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Ajouter au panierEtat : New.
Edité par Packt Publishing Limited, GB, 2022
ISBN 10 : 1804611301 ISBN 13 : 9781804611302
Langue: anglais
Vendeur : Rarewaves.com USA, London, LONDO, Royaume-Uni
EUR 70,14
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Ajouter au panierPaperback. Etat : New. Create end-to-end, reproducible feature engineering pipelines that can be deployed into production using open-source Python librariesKey FeaturesLearn 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 DescriptionFeature 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 learnImpute 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 forThis 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.
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
EUR 56,69
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Ajouter au panierEtat : As New. Unread book in perfect condition.
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
EUR 62,74
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Ajouter au panierTaschenbuch. Etat : 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.
EUR 38,23
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EUR 13,91
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Ajouter au panierpaperback. Etat : Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!