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Ajouter au panierEtat : very_good. Gently read. May have name of previous ownership, or ex-library edition. Binding tight; spine straight and smooth, with no creasing; covers clean and crisp. Minimal signs of handling or shelving. 100% GUARANTEE! Shipped with delivery confirmation, if you're not satisfied with purchase please return item for full refund. Ships USPS Media Mail.
Edité par Packt Publishing, Limited, 2017
ISBN 10 : 1785880519 ISBN 13 : 9781785880513
Langue: anglais
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Ajouter au panierPaperback. 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!
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Ajouter au panierEtat : New. pp. 556.
Edité par Packt Publishing 2017-06, 2017
ISBN 10 : 1785880519 ISBN 13 : 9781785880513
Langue: anglais
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Ajouter au panierEtat : New. Über den AutorrnrnDr. Uday Kamath is the chief data scientist at BAE Systems Applied Intelligence. He specializes in scalable machine learning and has spent 20 years in the domain of AML, fraud detection in financial crime, cyber security, .
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Ajouter au panierPaperback. Etat : New. New. book.
Edité par Packt Publishing Limited, 2017
ISBN 10 : 1785880519 ISBN 13 : 9781785880513
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Ajouter au panierPAP. Etat : New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Edité par Packt Publishing Limited, 2017
ISBN 10 : 1785880519 ISBN 13 : 9781785880513
Langue: anglais
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Ajouter au panierPAP. 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.
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Ajouter au panierEtat : New. Print on Demand pp. 556.
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Ajouter au panierEtat : New. PRINT ON DEMAND pp. 556.
Edité par Packt Publishing Limited, 2017
ISBN 10 : 1785880519 ISBN 13 : 9781785880513
Langue: anglais
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Ajouter au panierPaperback / softback. Etat : New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 940.
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Ajouter au panierTaschenbuch. Etat : Neu. Mastering Java Machine Learning | A Java developer's guide to implementing machine learning and big data architectures | Uday Kamath (u. a.) | Taschenbuch | Englisch | 2017 | Packt Publishing | EAN 9781785880513 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
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Ajouter au panierTaschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Become an advanced practitioner with this progressive set of master classes on application-oriented machine learningKey FeaturesComprehensive coverage of key topics in machine learning with an emphasis on both the theoretical and practical aspectsMore than 15 open source Java tools in a wide range of techniques, with code and practical usage.More than 10 real-world case studies in machine learning highlighting techniques ranging from data ingestion up to analyzing the results of experiments, all preparing the user for the practical, real-world use of tools and data analysis.Book DescriptionJava is one of the main languages used by practicing data scientists; much of the Hadoop ecosystem is Java-based, and it is certainly the language that most production systems in Data Science are written in. If you know Java, Mastering Machine Learning with Java is your next step on the path to becoming an advanced practitioner in Data Science.This book aims to introduce you to an array of advanced techniques in machine learning, including classification, clustering, anomaly detection, stream learning, active learning, semi-supervised learning, probabilistic graph modeling, text mining, deep learning, and big data batch and stream machine learning. Accompanying each chapter are illustrative examples and real-world case studies that show how to apply the newly learned techniques using sound methodologies and the best Java-based tools available today.On completing this book, you will have an understanding of the tools and techniques for building powerful machine learning models to solve data science problems in just about any domain.What you will learnMaster key Java machine learning libraries, and what kind of problem each can solve, with theory and practical guidance.Explore powerful techniques in each major category of machine learning such as classification, clustering, anomaly detection, graph modeling, and text mining.Apply machine learning to real-world data with methodologies, processes, applications, and analysis.Techniques and experiments developed around the latest specializations in machine learning, such as deep learning, stream data mining, and active and semi-supervised learning.Build high-performing, real-time, adaptive predictive models for batch- and stream-based big data learning using the latest tools and methodologies.Get a deeper understanding of technologies leading towards a more powerful AI applicable in various domains such as Security, Financial Crime, Internet of Things, social networking, and so on.Who this book is forThis book will appeal to anyone with a serious interest in topics in Data Science or those already working in related areas: ideally, intermediate-level data analysts and data scientists with experience in Java. Preferably, you will have experience with the fundamentals of machine learning and now have a desire to explore the area further, are up to grappling with the mathematical complexities of its algorithms, and you wish to learn the complete ins and outs of practical machine learning.