Carsten Lange – författare

This textbook is a comprehensive guide to machine learning and artificial intelligence tailored for students in business and economics. It takes a hands-on approach to teach machine learning, emphasizing practical applications over complex mathematical concepts. Students are not required to have advanced mathematics knowledge such as matrix algebra or calculus.

The author introduces machine learning algorithms, utilizing the widely used R language for statistical analysis. Each chapter includes examples, case studies, and interactive tutorials to enhance understanding. No prior programming knowledge is needed. The book leverages the tidymodels package, an extension of R, to streamline data processing and model workflows. This package simplifies commands, making the logic of algorithms more accessible by minimizing programming syntax hurdles. The use of tidymodels ensures a unified experience across various machine learning models.

With interactive tutorials that students can download and follow along at their own pace, the book provides a practical approach to apply machine learning algorithms to real-world scenarios.

In addition to the interactive tutorials, each chapter includes a Digital Resources section, offering links to articles, videos, data, and sample R code scripts. A companion website further enriches the learning and teaching experience: https://ai.lange-analytics.com.

This book is not just a textbook; it is a dynamic learning experience that empowers students and instructors alike with a practical and accessible approach to machine learning in business and economics.

Key Features:

This textbook is a comprehensive guide to machine learning and artificial intelligence tailored for students in business and economics. It takes a hands-on approach to teach machine learning, emphasizing practical applications over complex mathematical concepts. Students are not required to have advanced mathematics knowledge such as matrix algebra or calculus.

The author introduces machine learning algorithms, utilizing the widely used R language for statistical analysis. Each chapter includes examples, case studies, and interactive tutorials to enhance understanding. No prior programming knowledge is needed. The book leverages the tidymodels package, an extension of R, to streamline data processing and model workflows. This package simplifies commands, making the logic of algorithms more accessible by minimizing programming syntax hurdles. The use of tidymodels ensures a unified experience across various machine learning models.

With interactive tutorials that students can download and follow along at their own pace, the book provides a practical approach to apply machine learning algorithms to real-world scenarios.

In addition to the interactive tutorials, each chapter includes a Digital Resources section, offering links to articles, videos, data, and sample R code scripts. A companion website further enriches the learning and teaching experience: https://ai.lange-analytics.com.

This book is not just a textbook; it is a dynamic learning experience that empowers students and instructors alike with a practical and accessible approach to machine learning in business and economics.

Key Features:

Der vorliegende Band beschreibt sowohl die theoretischen als auch die empirischen Aspekte neuronaler Netze. Nach einer detaillierten, auch für Einsteiger geeigneten Einführung in die Funktionsweise neuronaler Netze, richtet sich der zweite Teil des Buches an Forscher, die ein neuronales Netz als Erwartungsbildungsmodul oder als Optimierungsmodul in volkswirtschaftliche Modelle integrieren wollen. Im dritten Teil des Buches schließlich wird am Beispiel der Geldnachfrage dargestellt, wie neuronale Netze für die Analyse und Prognose wirtschaftswissenschaftlicher Zusammenhänge eingesetzt werden können. Gängige Trainings- und Optimierungsverfahren werden vorgestellt, und es wird gezeigt, wie diese Verfahren in einem Simulator für neuronale Netze implementiert werden können. Die beiliegende CD enthält eine interaktive Version des Buches. Computer-Simulationen, Programmierbeispiele und Quellcode für die Programme können direkt aus dem Text aufgerufen und Schritt für Schritt nachvollzogen werden.