Willkommen, schön sind Sie da!
Logo Ex Libris

Python Feature Engineering Cookbook

  • E-Book (epub)
  • 372 Seiten
(0) Erste Bewertung abgeben
Bewertungen
(0)
(0)
(0)
(0)
(0)
Alle Bewertungen ansehen
Extract accurate information from data to train and improve machine learning models using NumPy, SciPy, pandas, and scikit-learn ... Weiterlesen
E-Books ganz einfach mit der kostenlosen Ex Libris-Reader-App lesen. Hier erhalten Sie Ihren Download-Link.
CHF 28.90
Download steht sofort bereit
Informationen zu E-Books
E-Books eignen sich auch für mobile Geräte (sehen Sie dazu die Anleitungen).
E-Books von Ex Libris sind mit Adobe DRM kopiergeschützt: Erfahren Sie mehr.
Weitere Informationen finden Sie hier.
Bestellung & Lieferung in eine Filiale möglich

Beschreibung

Extract accurate information from data to train and improve machine learning models using NumPy, SciPy, pandas, and scikit-learn librariesKey FeaturesDiscover solutions for feature generation, feature extraction, and feature selectionUncover the end-to-end feature engineering process across continuous, discrete, and unstructured datasetsImplement modern feature extraction techniques using Python's pandas, scikit-learn, SciPy and NumPy librariesBook DescriptionFeature 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.What you will learnSimplify your feature engineering pipelines with powerful Python packagesGet to grips with imputing missing valuesEncode categorical variables with a wide set of techniquesExtract insights from text quickly and effortlesslyDevelop features from transactional data and time series dataDerive new features by combining existing variablesUnderstand how to transform, discretize, and scale your variablesCreate informative variables from date and timeWho this book is forThis book is for machine learning professionals, AI engineers, data scientists, and NLP and reinforcement learning engineers who want to optimize and enrich their machine learning models with the best features. Knowledge of machine learning and Python coding will assist you with understanding the concepts covered in this book.

Produktinformationen

Titel: Python Feature Engineering Cookbook
Untertitel: Over 70 recipes for creating, engineering, and transforming features to build machine learning models
Autor:
EAN: 9781789807820
Digitaler Kopierschutz: Adobe-DRM
Format: E-Book (epub)
Hersteller: Packt Publishing
Anzahl Seiten: 372
Veröffentlichung: 22.01.2020
Dateigrösse: 5.6 MB