The fundamental algorithms in data mining and machine learning form the basis of data science, utilizing automated methods to analyze patterns and models for all kinds of data in applications ranging from scientific discovery to business analytics. This textbook for senior undergraduate and graduate courses provides a comprehensive, in-depth overview of data mining, machine learning and statistics, offering solid guidance for students, researchers, and practitioners. The book lays the foundations of data analysis, pattern mining, clustering, classification and regression, with a focus on the algorithms and the underlying algebraic, geometric, and probabilistic concepts. New to this second edition is an entire part devoted to regression methods, including neural networks and deep learning.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Mohammed J. Zaki is Professor of Computer Science at Rensselaer Polytechnic Institute, New York, where he also serves as Associate Department Head and Graduate Program Director. He has more than 250 publications and is an Associate Editor for the journal Data Mining and Knowledge Discovery. He is on the Board of Directors for Association for Computing Machinery's Special Interest Group on Knowledge Discovery and Data Mining (ACM SIGKDD). He has received the National Science Foundation CAREER Award, and the Department of Energy Early Career Principal Investigator Award. He is an ACM Distinguished Member, and IEEE Fellow.
Wagner Meira, Jr is Professor of Computer Science at Universidade Federal de Minas Gerais, Brazil, where he is currently the chair of the department. He has published more than 230 papers on data mining and parallel and distributed systems. He was leader of the Knowledge Discovery research track of InWeb and is currently Vice-chair of INCT-Cyber. He is on the editorial board of the journal Data Mining and Knowledge Discovery and was the program chair of SDM'16 and ACM WebSci'19. He has been a CNPq researcher since 2002. He has received an IBM Faculty Award and several Google Faculty Research Awards.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Vendeur : HPB-Red, Dallas, TX, Etats-Unis
hardcover. Etat : Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority! N° de réf. du vendeur S_454591514
Quantité disponible : 1 disponible(s)
Vendeur : Books From California, Simi Valley, CA, Etats-Unis
hardcover. Etat : Fine. N° de réf. du vendeur mon0003890271
Quantité disponible : 1 disponible(s)
Vendeur : Textbooks_Source, Columbia, MO, Etats-Unis
hardcover. Etat : Good. 2nd Edition. Ships in a BOX from Central Missouri! May not include working access code. Will not include dust jacket. Has used sticker(s) and some writing or highlighting. UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes). N° de réf. du vendeur 002302499U
Quantité disponible : 1 disponible(s)
Vendeur : WorldofBooks, Goring-By-Sea, WS, Royaume-Uni
Paperback. Etat : Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged. N° de réf. du vendeur GOR011990365
Quantité disponible : 1 disponible(s)
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Etat : As New. Unread book in perfect condition. N° de réf. du vendeur 37655846
Quantité disponible : Plus de 20 disponibles
Vendeur : Book Grocer, Tullamarine, VIC, Australie
Hardback. Mohammed J. Zaki (Rensselaer Polytechnic Institute, New York), Cambridge University Press. The fundamental algorithms in data mining and machine learning form the basis of data science, utilizing automated methods to analyze patterns and models for all kinds of data in applications ranging from scientific discovery to business analytics. This textbook for senior undergraduate and graduate courses provides a comprehensive, in-depth overview of data mining, machine learning and statistics, offering solid guidance for students, researchers, and practitioners. The book lays the foundations of data analysis, pattern mining, clustering, classification and regression, with a focus on the algorithms and the underlying algebraic, geometric, and probabilistic concepts. New to this second edition is an entire part devoted to regression methods, including neural networks and deep learning. Hardback. N° de réf. du vendeur 9781108473989-RETAIL
Quantité disponible : 1 disponible(s)
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Etat : good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers. N° de réf. du vendeur 37655846-5
Quantité disponible : 1 disponible(s)
Vendeur : Lucky's Textbooks, Dallas, TX, Etats-Unis
Etat : New. N° de réf. du vendeur ABLIING23Mar2317530284417
Quantité disponible : Plus de 20 disponibles
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Etat : New. N° de réf. du vendeur 37655846-n
Quantité disponible : Plus de 20 disponibles
Vendeur : TextbookRush, Grandview Heights, OH, Etats-Unis
Etat : Brand New. N° de réf. du vendeur 55682024
Quantité disponible : 3 disponible(s)