ros frederic (17 Ergebnisse)

Softcover. Zustand: Comme neuf. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, As new. Ammareal gives back up to 15% of this item's net price to charity organizations.

Paperback. Zustand: Brand New. 52 pages. 8.66x5.91x0.12 inches. In Stock.

Taschenbuch. Zustand: Neu. A new density-based sampling for clustering algorithm | Frederic Ros (u. a.) | Taschenbuch | 52 S. | Englisch | 2016 | Scholars' Press | EAN 9783659841354 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Zustand: Bon. Merci, votre achat aide à financer des programmes de lutte contre l'illettrisme.

Zustand: New. In.

Zustand: New. In.

Zustand: New. In.

Paperback. Zustand: Brand New. 9.26x6.11 inches. In Stock.

Gebunden. Zustand: New.

Taschenbuch. Zustand: Neu. Sampling Techniques for Supervised or Unsupervised Tasks | Frédéric Ros (u. a.) | Taschenbuch | Unsupervised and Semi-Supervised Learning | xiii | Englisch | 2020 | Springer | EAN 9783030293512 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Taschenbuch. Zustand: Neu. Feature and Dimensionality Reduction for Clustering with Deep Learning | Frederic Ros (u. a.) | Taschenbuch | Unsupervised and Semi-Supervised Learning | xi | Englisch | 2025 | Springer | EAN 9783031487453 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book describes in detail sampling techniques that can be used for unsupervised and supervised cases, with a focus on sampling techniques for machine learning algorithms. It covers theory and models of sampling methods for managing scalability and the 'curse of dimensionality', their implementations, evaluations, and applications. A large part of the book is dedicated to database comprising standard feature vectors, and a special section is reserved to the handling of more complex objects and dynamic scenarios. The book is ideal for anyone teaching or learning pattern recognition and interesting teaching or learning pattern recognition and is interested in the big data challenge. It provides an accessible introduction to the field and discusses the state of the art concerning sampling techniques for supervised and unsupervised task.Provides a comprehensive description of sampling techniques for unsupervised and supervised tasks;Describe implementationand evaluation of algorithms that simultaneously manage scalable problems and curse of dimensionality;Addresses the role of sampling in dynamic scenarios, sampling when dealing with complex objects, and new challenges arising from big data. 'This book represents a timely collection of state-of-the art research of sampling techniques, suitable for anyone who wants to become more familiar with these helpful techniques for tackling the big data challenge.'M. Emre Celebi, Ph.D., Professor and Chair, Department of Computer Science, University of Central Arkansas'In science the difficulty is not to have ideas, but it is to make them work'From Carlo Rovelli.

Hardcover. Zustand: Brand New. 248 pages. 9.25x6.10x0.75 inches. In Stock.

Hardcover. Zustand: Brand New. 279 pages. 9.25x6.10x0.91 inches. In Stock.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book describes in detail sampling techniques that can be used for unsupervised and supervised cases, with a focus on sampling techniques for machine learning algorithms. It covers theory and models of sampling methods for managing scalability and the 'curse of dimensionality', their implementations, evaluations, and applications. A large part of the book is dedicated to database comprising standard feature vectors, and a special section is reserved to the handling of more complex objects and dynamic scenarios. The book is ideal for anyone teaching or learning pattern recognition and interesting teaching or learning pattern recognition and is interested in the big data challenge. It provides an accessible introduction to the field and discusses the state of the art concerning sampling techniques for supervised and unsupervised task.Provides a comprehensive description of sampling techniques for unsupervised and supervised tasks;Describe implementationand evaluation of algorithms that simultaneously manage scalable problems and curse of dimensionality;Addresses the role of sampling in dynamic scenarios, sampling when dealing with complex objects, and new challenges arising from big data. 'This book represents a timely collection of state-of-the art research of sampling techniques, suitable for anyone who wants to become more familiar with these helpful techniques for tackling the big data challenge.'M. Emre Celebi, Ph.D., Professor and Chair, Department of Computer Science, University of Central Arkansas'In science the difficulty is not to have ideas, but it is to make them work'From Carlo Rovelli.

Zustand: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | This book describes in detail sampling techniques that can be used for unsupervised and supervised cases, with a focus on sampling techniques for machine learning algorithms. It covers theory and models of sampling methods for managing scalability and the ¿curse of dimensionality¿, their implementations, evaluations, and applications. A large part of the book is dedicated to database comprising standard feature vectors, and a special section is reserved to the handling of more complex objects and dynamic scenarios. The book is ideal for anyone teaching or learning pattern recognition and interesting teaching or learning pattern recognition and is interested in the big data challenge. It provides an accessible introduction to the ¿eld and discusses the state of the art concerning sampling techniques for supervised and unsupervised task.Provides a comprehensive description of sampling techniques for unsupervised and supervised tasks;Describe implementationand evaluation of algorithms that simultaneously manage scalable problems and curse of dimensionality;Addresses the role of sampling in dynamic scenarios, sampling when dealing with complex objects, and new challenges arising from big data. "This book represents a timely collection of state-of-the art research of sampling techniques, suitable for anyone who wants to become more familiar with these helpful techniques for tackling the big data challenge."M. Emre Celebi, Ph.D., Professor and Chair, Department of Computer Science, University of Central Arkansas"In science the difficulty is not to have ideas, but it is to make them work"From Carlo Rovelli.

Zustand: Buen estado. 1ª Edició. Plegado Buen estado.