Artificial Intelligence and Machine Learning with R: Applications in the Field of Business Analytics - Softcover

Heesen, Bernd

Softcover

ISBN 10: 3658453915 ISBN 13: 9783658453916

Verlag: Springer, 2024

Inhaltsangabe

In a VUCA world, which is becoming increasingly volatile, uncertain, and complex, companies, organizations, and states must respond promptly and adequately to the respective situations. Making decisions based on past experiences is less successful in these times than having an accurate understanding of current conditions. The importance of empirical sciences, continuous environmental observation, timely analysis of causal relationships, and deriving new insights from them is increasing. From this, it can be deduced which measures are likely to achieve one's goals with predictable probability, such as which price for an offer generates the desired demand or which marketing measure reaches the desired target group.

Where classical statistics were once used for calculations and predictions, today free (open source) tools like R allow data in various formats and from any number of sources to be read in, processed, and analyzed using methods of Artificial Intelligence and Machine Learning. The results can then be perfectly visualized so that decision-makers can benefit quickly and effectively.

The age of Data Science has arrived. Digitalization is more than a buzzword or a promise; it is actionable and usable for everyone.

This book teaches you, based on the latest version of R at the time of publication, how to use Artificial Intelligence and Machine Learning in Industry 4.0.

Über diesen Titel

Über die Autorin bzw. den Autor

Bernd Heesen is a professor at the Faculty of Economics at Ansbach University of Applied Sciences in Bavaria. Before his tenure at the university, he worked for more than 10 years as a business consultant both domestically and internationally. He continues to advise companies on the use of IT innovations.

Von der hinteren Coverseite

This book teaches you, based on the open-source programming language R, how to read, process, and analyze data from various formats and sources, and how to use Artificial Intelligence and Machine Learning in your company. It specifically explains the three types of Machine Learning and selected, widely-used algorithms that form the basis of Artificial Intelligence. Additionally, the author provides you with the datasets used through his R package "machinelearning," so you can run the code examples presented in the book yourself. The package also includes interactive self-learning tutorials for R.

Contents

• Benefits of Machine Learning and Artificial Intelligence
• Best Practices
• Fundamentals of the R Programming Language
• Fundamentals of Machine Learning with R, including preprocessing, exploratory data analysis, modeling, evaluation, and parameter tuning
• Application of Machine Learning with R for predictions, classification, clustering, and recommendation systems

The Author

Bernd Heesen is a professor at the Faculty of Economics at Ansbach University of Applied Sciences in Bavaria. Before his tenure at the university, he worked for more than 10 years as a business consultant both domestically and internationally. He continues to advise companies on the use of IT innovations.

The translation was done with the help of artificial intelligence. A subsequent human revision was done primarily in terms of content.

This book is a translation of an original German edition. The translation was done with the help of artificial intelligence (machine translation by the service DeepL.com). A subsequent human revision was done primarily in terms of content, so that the book will read stylistically differently from a conventional translation.

Details zur Ausgabe

• Verlag: Springer
• Erscheinungsdatum: 2024
• Sprache: Englisch
• ISBN 10: 3658453915
• ISBN 13: 9783658453916
• Einband: Taschenbuch
• Anzahl der Seiten: 506
• Kontakt zum Hersteller: ProductSafety@springernature.com; ProductSafety@springernature.com; ; Poststr. 9; Darmstadt; 64293; Deutschland