Overview

"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"

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9783982576305

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Reviews

"The book ""Machine Learning with R"" by Prof. Schell illustrates statistics comprehensively. It provides the reader with statistical applications in the context of artificial intelligence and digitization and is extremely user-oriented. Particularly noteworthy here is the understandable formulation, a reading flow based on understandable examples and accompanying illustrations (e.g. plots), so that even complex issues are presented in a very memorable and comprehensible manner. The introductory questions that specify the facts are also helpful, as are the prepared tasks for learning about and experiencing practical application. The book is currently being used in a variety of ways in our research and project work in the field of data science and smart logistics. Prof. Schell has delivered a user-oriented manual that provides valuable assistance to users of R and thus statistical approaches in the field of artificial intelligence with a focus on analysis and interpretation of the underlying facts at different application levels. Prof. Dr. Marc Dressler"

Author Information

- Software developer at BBC AG and SAP AG- Professor at Kaiserslautern University of Applied Sciences

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