Python feature engineering cookbook : over 70 recipes for creating, engineering, and transforming features to build machine learning models /

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"Extract accurate information from data to train and improve machine learning models using NumPy, SciPy, pandas, and scikit-learn libraries Key Features Discover solutions for feature generation, feature extraction, and feature selection Uncover the end-to-end feature engineering process across...

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Détails bibliographiques
Cote:Libro Electrónico
Auteur principal: Galli, Soledad (Auteur)
Format: Électronique eBook
Langue:Inglés
Publié: Birmingham, UK : Packt Publishing, 2020.
Sujets:
Python (Computer program language)
Application software > Development.
Machine learning.
Python (Langage de programmation)
Logiciels d'application > Développement.
Apprentissage automatique.
Data capture & analysis.
Data mining.
Information architecture.
Database design & theory.
Computers > Data Processing.
Computers > Database Management > Data Mining.
Computers > Data Modeling & Design.
Accès en ligne:Texto completo (Requiere registro previo con correo institucional)
Table des matières:
  • Preface
  • Foreseeing Variable Problems When Building ML Models
  • Imputing Missing Data
  • Encoding Categorical Variables
  • Transforming Numerical Variables
  • Performing Variable Discretization
  • Working with Outliers
  • Deriving Features from Dates and Time Variables
  • Performing Feature Scaling
  • Applying Mathematical Computations to Features
  • Creating Features with Transactional and Time Series Data
  • Extracting Features from Text Variables

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