Machine learning deep computational (74 résultats)

paperback. Etat : New. Brand new book, sourced directly from publisher. Dispatch time is 7-8 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Etat : New. In English.

Etat : New.

Etat : New. In English.

Hardcover. Etat : Very Good. No Jacket. 1st Edition. 2023.Hardcover.Very good condition. 288 pages.Ships from Japan.Usually ships in 1-2 working days.

Hardcover. Etat : New. Brand new book, sourced directly from publisher. Dispatch time is 7-8 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Etat : New. A brand new book in pristine condition. Showing zero signs of shelf wear, creases, or damage.

Etat : New.

Etat : New.

Etat : New. In English.

Taschenbuch. Etat : Neu. Machine Learning and Deep Learning in Computational Toxicology | Huixiao Hong | Taschenbuch | Computational Methods in Engineering & the Sciences | xix | Englisch | 2024 | Springer | EAN 9783031207327 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

paperback. Etat : New. New .Ships From Multiple Locations. book.

Etat : New.

Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is a collection of machine learning and deep learning algorithms, methods, architectures, and software tools that have been developed and widely applied in predictive toxicology. It compiles a set of recent applications using state-of-the-art machine learning and deep learning techniques in analysis of a variety of toxicological endpoint data. The contents illustrate those machine learning and deep learning algorithms, methods, and software tools and summarise the applications of machine learning and deep learning in predictive toxicology with informative text, figures, and tables that are contributed by the first tier of experts. One of the major features is the case studies of applications of machine learning and deep learning in toxicological research that serve as examples for readers to learn how to apply machine learning and deep learning techniques in predictive toxicology. This book is expected to provide a reference for practical applications of machine learning anddeep learning in toxicological research. It is a useful guide for toxicologists, chemists, drug discovery and development researchers, regulatory scientists, government reviewers, and graduate students. The main benefit for the readers is understanding the widely used machine learning and deep learning techniques and gaining practical procedures for applying machine learning and deep learning in predictive toxicology.…

Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is a collection of machine learning and deep learning algorithms, methods, architectures, and software tools that have been developed and widely applied in predictive toxicology. It compiles a set of recent applications using state-of-the-art machine learning and deep learning techniques in analysis of a variety of toxicological endpoint data. The contents illustrate those machine learning and deep learning algorithms, methods, and software tools and summarise the applications of machine learning and deep learning in predictive toxicology with informative text, figures, and tables that are contributed by the first tier of experts. One of the major features is the case studies of applications of machine learning and deep learning in toxicological research that serve as examples for readers to learn how to apply machine learning and deep learning techniques in predictive toxicology. This book is expected to provide a reference for practical applications of machine learning anddeep learning in toxicological research. It is a useful guide for toxicologists, chemists, drug discovery and development researchers, regulatory scientists, government reviewers, and graduate students. The main benefit for the readers is understanding the widely used machine learning and deep learning techniques and gaining practical procedures for applying machine learning and deep learning in predictive toxicology.…

Etat : New. In English.

Etat : New. 1st ed. 2023 edition NO-PA16APR2015-KAP.

Etat : New. 1st ed. 2023 edition NO-PA16APR2015-KAP.

Etat : New.

Etat : New.

Taschenbuch. Etat : Neu. Machine Learning, Deep Learning and Computational Intelligence for Wireless Communication | Proceedings of MDCWC 2020 | E. S. Gopi | Taschenbuch | Lecture Notes in Electrical Engineering | xix | Englisch | 2022 | Springer | EAN 9789811602917 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.…

Etat : New. In English.

Etat : New. In English.

Etat : As New. Unread book in perfect condition.

Etat : As New. Unread book in perfect condition.

Hardcover. Etat : Brand New. 296 pages. 9.25x6.10x0.75 inches. In Stock.

Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is a collection of best selected research papers presented at the Conference on Machine Learning, Deep Learning and Computational Intelligence for Wireless Communication (MDCWC 2020) held during October 22nd to 24th 2020, at the Department of Electronics and Communication Engineering, National Institute of Technology Tiruchirappalli, India. The presented papers are grouped under the following topics (a) Machine Learning, Deep learning and Computational intelligence algorithms (b)Wireless communication systems and (c) Mobile data applications and are included in the book. The topics include the latest research and results in the areas of network prediction, traffic classification, call detail record mining, mobile health care, mobile pattern recognition, natural language processing, automatic speech processing, mobility analysis, indoor localization, wireless sensor networks (WSN), energy minimization, routing, scheduling, resource allocation, multiple access, powercontrol, malware detection, cyber security, flooding attacks detection, mobile apps sniffing, MIMO detection, signal detection in MIMO-OFDM, modulation recognition, channel estimation, MIMO nonlinear equalization, super-resolution channel and direction-of-arrival estimation. The book is a rich reference material for academia and industry.…

Etat : New. In English.

Etat : New.

Etat : New.