Ebook Free An Introduction to Machine Learning

Ebook Free An Introduction to Machine Learning

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An Introduction to Machine Learning

Ebook Free An Introduction to Machine Learning

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Pressestimmen

“The presentation is mainly empirical, but precise and pedagogical, as each concept introduced is followed by a set of questions which allows the reader to check immediately whether they understand the topic. Each chapter ends with a historical summary and a series of computer assignments. … this book could serve as textbook for an undergraduate introductory course on machine learning … .” (Gilles Teyssière, Mathematical Reviews, April, 2017) “This book describes ongoing human-computer interaction (HCI) research and practical applications. … These techniques can be very useful in AR/VR development projects, and some of these chapters can be used as examples and guides for future research.” (Miguel A. Garcia-Ruiz, Computing Reviews, January, 2019)

Buchrückseite

This textbook presents fundamental machine learning concepts in an easy to understand manner by providing practical advice, using straightforward examples, and offering engaging discussions of relevant applications. The main topics include Bayesian classifiers, nearest-neighbor classifiers, linear and polynomial classifiers, decision trees, neural networks, and support vector machines. Later chapters show how to combine these simple tools by way of “boosting,” how to exploit them in more complicated domains, and how to deal with diverse advanced practical issues. One chapter is dedicated to the popular genetic algorithms. This revised edition contains three entirely new chapters on critical topics regarding the pragmatic application of machine learning in industry. The chapters examine multi-label domains, unsupervised learning and its use in deep learning, and logical approaches to induction as well as Inductive Logic Programming. Numerous chapters have been expanded, and the presentation of the material has been enhanced. The book contains many new exercises, numerous solved examples, thought-provoking experiments, and computer assignments for independent work.

Alle Produktbeschreibungen

Produktinformation

Gebundene Ausgabe: 348 Seiten

Verlag: Springer; Auflage: 2nd ed. 2017 (8. September 2017)

Sprache: Englisch

ISBN-10: 9783319639123

ISBN-13: 978-3319639123

ASIN: 3319639129

Größe und/oder Gewicht:

15,6 x 2,1 x 23,4 cm

Durchschnittliche Kundenbewertung:

Schreiben Sie die erste Bewertung

Amazon Bestseller-Rang:

Nr. 384.525 in Fremdsprachige Bücher (Siehe Top 100 in Fremdsprachige Bücher)

An Introduction to Machine Learning PDF
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An Introduction to Machine Learning PDF

An Introduction to Machine Learning PDF

An Introduction to Machine Learning PDF

An Introduction to Machine Learning PDF