Hands-On Ensemble Learning with Python
George Kyriakides
Vendu par AHA-BUCH GmbH, Einbeck, Allemagne
Vendeur AbeBooks depuis 14 août 2006
Neuf(s) - Couverture souple
Etat : Neuf
Quantité disponible : 1 disponible(s)
Ajouter au panierVendu par AHA-BUCH GmbH, Einbeck, Allemagne
Vendeur AbeBooks depuis 14 août 2006
Etat : Neuf
Quantité disponible : 1 disponible(s)
Ajouter au paniernach der Bestellung gedruckt Neuware - Printed after ordering.
N° de réf. du vendeur 9781789612851
Combine popular machine learning techniques to create ensemble models using Python
Ensembling is a technique of combining two or more similar or dissimilar machine learning algorithms to create a model that delivers superior predictive power. This book will demonstrate how you can use a variety of weak algorithms to make a strong predictive model.
With its hands-on approach, you'll not only get up to speed on the basic theory but also the application of various ensemble learning techniques. Using examples and real-world datasets, you'll be able to produce better machine learning models to solve supervised learning problems such as classification and regression. Furthermore, you'll go on to leverage ensemble learning techniques such as clustering to produce unsupervised machine learning models. As you progress, the chapters will cover different machine learning algorithms that are widely used in the practical world to make predictions and classifications. You'll even get to grips with the use of Python libraries such as scikit-learn and Keras for implementing different ensemble models.
By the end of this book, you will be well-versed in ensemble learning, and have the skills you need to understand which ensemble method is required for which problem, and successfully implement them in real-world scenarios.
This book is for data analysts, data scientists, machine learning engineers and other professionals who are looking to generate advanced models using ensemble techniques. An understanding of Python code and basic knowledge of statistics is required to make the most out of this book.
George Kyriakides is a Ph.D. researcher, studying distributed neural architecture search. His interests and experience include automated generation and optimization of predictive models for a wide array of applications, such as image recognition, time series analysis, and financial applications. He holds an M.Sc. in computational methods and applications, and a B.Sc. in applied informatics, both from the University of Macedonia, Thessaloniki, Greece.
Konstantinos G. Margaritis has been a teacher and researcher in computer science for more than 30 years. His research interests include parallel and distributed computing as well as computational intelligence and machine learning. He holds an M.Eng. in electrical engineering (Aristotle University of Thessaloniki, Greece), as well as an M.Sc. and a Ph.D. in computer science (Loughborough University, UK). He is a professor at the Department of Applied Informatics, University of Macedonia, Thessaloniki, Greece.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Visitez la page d’accueil du vendeur
Conditions générales et informations client
I. Conditions générales
§ 1 Dispositions de base
(1) Les conditions générales suivantes s?appliquent à tous les contrats que vous concluez avec nous en tant que fournisseur (AHA-BUCH GmbH) via les plateformes Internet AbeBooks et/ou ZVAB. Sauf accord contraire, l?inclusion de l?une de vos propres conditions générales que vous utilisez sera contestée
(2) Un consommateur au sens des règlements suivants est toute personne physique qui conclut une transact...
Pour plus d'informationNous expédions votre commande après les avoir reçues
pour les articles disponibles au plus tard 24 heures,
pour les articles avec un approvisionnement de nuit au plus tard 48 heures.
Dans le cas où nous devons commander un article auprès de notre fournisseur, notre délai d’expédition dépend de la date de réception des articles, mais les articles seront expédiés le jour même.
Notre objectif est d’envoyer les articles commandés de la manière la plus rapide, mais aussi la plus efficace et la plus sécurisée à nos clients.