Edité par Engineering Science Reference, 2021
ISBN 10 : 1799866599 ISBN 13 : 9781799866596
Langue: anglais
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
EUR 300,24
Quantité disponible : Plus de 20 disponibles
Ajouter au panierEtat : New. In.
Edité par Engineering Science Reference, 2021
ISBN 10 : 1799866599 ISBN 13 : 9781799866596
Langue: anglais
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
EUR 300,23
Quantité disponible : Plus de 20 disponibles
Ajouter au panierEtat : New.
Edité par Engineering Science Reference, 2021
ISBN 10 : 1799866599 ISBN 13 : 9781799866596
Langue: anglais
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
EUR 320,04
Quantité disponible : Plus de 20 disponibles
Ajouter au panierEtat : New.
Edité par Engineering Science Reference, 2021
ISBN 10 : 1799866599 ISBN 13 : 9781799866596
Langue: anglais
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
EUR 341,53
Quantité disponible : Plus de 20 disponibles
Ajouter au panierEtat : As New. Unread book in perfect condition.
Edité par Engineering Science Reference, 2021
ISBN 10 : 1799866599 ISBN 13 : 9781799866596
Langue: anglais
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
EUR 340,21
Quantité disponible : Plus de 20 disponibles
Ajouter au panierEtat : As New. Unread book in perfect condition.
Vendeur : PBShop.store UK, Fairford, GLOS, Royaume-Uni
EUR 312,99
Quantité disponible : Plus de 20 disponibles
Ajouter au panierHRD. Etat : New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Vendeur : PBShop.store US, Wood Dale, IL, Etats-Unis
EUR 325,34
Quantité disponible : Plus de 20 disponibles
Ajouter au panierHRD. Etat : New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Edité par Engineering Science Reference, 2020
ISBN 10 : 1799866599 ISBN 13 : 9781799866596
Langue: anglais
Vendeur : moluna, Greven, Allemagne
EUR 326
Quantité disponible : Plus de 20 disponibles
Ajouter au panierEtat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. KlappentextrnrnIn today s digital world, the huge amount of data being generated is unstructured, messy, and chaotic in nature. Dealing with such data, and attempting to unfold the meaningful information, can be a challenging task. Feature engin.
Edité par Engineering Science Reference, 2021
ISBN 10 : 1799866599 ISBN 13 : 9781799866596
Langue: anglais
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
EUR 405,79
Quantité disponible : 1 disponible(s)
Ajouter au panierBuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In today's digital world, the huge amount of data being generated is unstructured, messy, and chaotic in nature. Dealing with such data, and attempting to unfold the meaningful information, can be a challenging task. Feature engineering is a process to transform such data into a suitable form that better assists with interpretation and visualization. Through this method, the transformed data is more transparent to the machine learning models, which in turn causes better prediction and analysis of results. Data science is crucial for the data scientist to assess the trade-offs of their decisions regarding the effectiveness of the machine learning model implemented. Investigating the demand in this area today and in the future is a necessity. The Handbook of Research on Automated Feature Engineering and Advanced Applications in Data Science provides an in-depth analysis on both the theoretical and the latest empirical research findings on how features can be extracted and transformed from raw data. The chapters will introduce feature engineering and the recent concepts, methods, and applications with the use of various data types, as well as examine the latest machine learning applications on the data. While highlighting topics such as detection, tracking, selection techniques, and prediction models using data science, this book is ideally intended for research scholars, big data scientists, project developers, data analysts, and computer scientists along with practitioners, researchers, academicians, and students interested in feature engineering and its impact on data.