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Machine Learning
58,99 € *
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This book covers the field of machine learning, which is the study of algorithms that allow computer programs to automatically improve through experience. The book is intended to support upper level undergraduate and introductory level graduate courses in machine learning.

Anbieter: buecher.de
Stand: 06.09.2019
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Machine Learning
13,99 € *
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Today, machine learning underlies a range of applications we use every day, from product recommendations to voice recognition-as well as some we don´t yet use everyday, including driverless cars. It is the basis of the new approach in computing where we do not write programs but collect data; the idea is to learn the algorithms for the tasks automatically from data. As computing devices grow more ubiquitous, a larger part of our lives and work is recorded digitally, and as ´´Big Data´´ has gotten bigger, the theory of machine learning-the foundation of efforts to process that data into knowledge-has also advanced. In this book, machine learning expert Ethem Alpaydin offers a concise overview of the subject for the general reader, describing its evolution, explaining important learning algorithms, and presenting example applications.

Anbieter: buecher.de
Stand: 06.09.2019
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Learning SPARQL
26,99 € *
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Gain hands-on experience with SPARQL, the RDF query language that?s bringing new possibilities to semantic web, linked data, and big data projects. This updated and expanded edition shows you how to use SPARQL 1.1 with a variety of tools to retrieve, manipulate, and federate data from the public web as well as from private sources. Author Bob DuCharme has you writing simple queries right away before providing background on how SPARQL fits into RDF technologies. Using short examples that you can run yourself with open source software, you?ll learn how to update, add to, and delete data in RDF datasets. * Get the big picture on RDF, linked data, and the semantic web * Use SPARQL to find bad data and create new data from existing data * Use datatype metadata and functions in your queries * Learn techniques and tools to help your queries run more efficiently * Use RDF Schemas and OWL ontologies to extend the power of your queries * Discover the roles that SPARQL can play in your applications

Anbieter: buecher.de
Stand: 06.09.2019
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Learning Agile
30,99 € *
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Agile revolutionized the way people think about developing software, but there are literally dozens of ways that you can ´´go agile.´´ While one team may find a particular agile practice easy to use, another team may find the same practice devilishly difficult. This book demystifies agile methodologies: why they´re designed the way they are, what problems they address, and the values, principles, and ideas they embody. Learning Agile helps you recognize the principles that apply to development problems specific to your team, company, and projects. You´ll discover how to use that information to guide your choice of methodologies and practices. With this book you´ll learn: Values that effective software teams possess The methodologies that embody those values The practices that make up those methodologies And principles that help you bring those values, methodologies, and practices to your team and your company

Anbieter: buecher.de
Stand: 15.09.2019
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Reinforcement Learning
57,99 € *
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The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence.

Anbieter: buecher.de
Stand: 16.09.2019
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Reinforcement Learning
53,99 € *
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Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field´s intellectual foundations to the most recent developments and applications.

Anbieter: buecher.de
Stand: 08.09.2019
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Deep Learning
65,99 € *
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Anbieter: buecher.de
Stand: 16.09.2019
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Learning Processing
36,99 € *
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Teaches you the basic building blocks of programming needed to create advanced graphics applications including interactive art, live video processing, and data visualization. This title offers graphic and web designers working with the Processing programming environment instructions on the basic principles of the language.

Anbieter: buecher.de
Stand: 14.09.2019
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Deep Learning. Das umfassende Handbuch
80,00 € *
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Mathematische Grundlagen für Machine und Deep Learning Umfassende Behandlung zeitgemäßer Verfahren: tiefe Feedforward-Netze, Regularisierung, Performance-Optimierung sowie CNNs, Rekurrente und Rekursive Neuronale Netze Zukunftsweisende Deep-Learning-Ansätze sowie von Ian Goodfellow neu entwickelte Konzepte wie Generative Adversarial Networks Deep Learning ist ein Teilbereich des Machine Learnings und versetzt Computer in die Lage, aus Erfahrungen zu lernen. Dieses Buch behandelt umfassend alle Aspekte, die für den Einsatz und die Anwendung von Deep Learning eine Rolle spielen: In Teil I erläutern die Autoren die mathematischen Grundlagen für Künstliche Intelligenz, Neuronale Netze, Machine Learning und Deep Learning. In Teil II werden die aktuellen in der Praxis genutzten Verfahren und Algorithmen behandelt. In Teil III geben die Autoren Einblick in aktuelle Forschungsansätze und zeigen neue zukunftsweisende Verfahren auf. Dieses Buch richtet sich an Studenten und alle, die sich in der Forschung mit Deep Learning beschäftigen sowie an Softwareentwickler und Informatiker, die Deep Learning für eigene Produkte oder Plattformen einsetzen möchten. Dabei werden Grundkenntnisse in Mathematik, Informatik und Programmierung vorausgesetzt. Teil I: Angewandte Mathematik und Grundlagen für das Machine Learning Lineare Algebra Wahrscheinlichkeits- und Informationstheorie Bayessche Statistik Numerische Berechnung Teil II: Deep-Learning-Verfahren Tiefe Feedforward-Netze Regularisierung Optimierung beim Trainieren tiefer Modelle Convolutional Neural Networks Sequenzmodellierung für Rekurrente und Rekursive Netze Praxisorientierte Methodologie Anwendungen: Computer Vision, Spracherkennung, Verarbeitung natürlicher Sprache Teil III: Deep-Learning-Forschung Lineare Faktorenmodelle Autoencoder Representation Learning Probabilistische graphische Modelle Monte-Carlo-Verfahren Die Partitionsfunktion Approximative Inferenz Tiefe generative Modelle wie Restricted Boltzmann Machines, Deep-Belief-Netze, Gerichtete Generative Netze, Variational Autoencoder u.v.m.

Anbieter: buecher.de
Stand: 06.09.2019
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