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Beschreibung
How do you teach computers to learn from data?

This hands-on introduction teaches the basics of machine learning with R, H2O and Keras using numerous examples. You will be able to select the appropriate approach and apply it to your own questions such as image classification or predictions.
Since erroneous data can jeopardize learning success, special attention is paid to data preparation and analysis. For this purpose, R provides highly developed and scientifically sound analysis libraries, the functionality and application of which are shown.

You will learn for which applications statistical methods such as regression, classification, factor, cluster and time series analysis are sufficient and when it is better to use neural networks such as e.g. B. CNNs or RNNs should work. The H20 framework and Keras are used here.

Examples show how you can analyze stumbling blocks in the learning process or how to avoid them from the outset. You will also learn under what circumstances you can reuse the results of machine learning and how to do this.

This book is a translation of "Maschinelles Lernen mit R", Carl Hanser Verlag, ISBN 978-3446471658
How do you teach computers to learn from data?

This hands-on introduction teaches the basics of machine learning with R, H2O and Keras using numerous examples. You will be able to select the appropriate approach and apply it to your own questions such as image classification or predictions.
Since erroneous data can jeopardize learning success, special attention is paid to data preparation and analysis. For this purpose, R provides highly developed and scientifically sound analysis libraries, the functionality and application of which are shown.

You will learn for which applications statistical methods such as regression, classification, factor, cluster and time series analysis are sufficient and when it is better to use neural networks such as e.g. B. CNNs or RNNs should work. The H20 framework and Keras are used here.

Examples show how you can analyze stumbling blocks in the learning process or how to avoid them from the outset. You will also learn under what circumstances you can reuse the results of machine learning and how to do this.

This book is a translation of "Maschinelles Lernen mit R", Carl Hanser Verlag, ISBN 978-3446471658
Über den Autor
- Software developer at BBC AG and SAP AG- Professor at Kaiserslautern University of Applied Sciences
Details
Erscheinungsjahr: 2023
Fachbereich: Datenkommunikation, Netze & Mailboxen
Genre: Informatik, Mathematik, Medizin, Naturwissenschaften, Technik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
ISBN-13: 9783982576305
ISBN-10: 398257630X
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Schell, Uli
Hersteller: Self Publishing
Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, D-36244 Bad Hersfeld, gpsr@libri.de
Maße: 229 x 152 x 25 mm
Von/Mit: Uli Schell
Erscheinungsdatum: 22.09.2023
Gewicht: 0,653 kg
Artikel-ID: 127740912

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