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Data Modeling : From Physical Processes to Machine Learning / by Elmar Rueckert.
Springer Nature - Springer Computer Science eBooks 2026 English International Available online
View online- Format:
- Book
- Author/Creator:
- Rueckert, Elmar.
- Series:
- Computer Science Series
- Language:
- English
- Subjects (All):
- Data mining.
- Machine learning.
- Artificial intelligence--Data processing.
- Artificial intelligence.
- Information visualization.
- Data Mining and Knowledge Discovery.
- Machine Learning.
- Data Science.
- Data and Information Visualization.
- Local Subjects:
- Data Mining and Knowledge Discovery.
- Machine Learning.
- Data Science.
- Data and Information Visualization.
- Physical Description:
- 1 online resource (131 pages)
- Edition:
- 1st ed. 2026.
- Place of Publication:
- Singapore : Springer Nature Singapore : Imprint: Springer, 2026.
- Summary:
- This book presents the fundamental theories, concepts, and methods of data modeling, bridging physical processes with machine learning predictions. It covers topics such as data collection, storage, analysis, and practical applications of machine learning. The textbook is designed for first-semester undergraduate students. The material introduces essential concepts in a clear and approachable way, offering a foundation in data-driven decision-making and predictive modeling. The content is aligned with the lectures of Prof. Dr. Elmar Rueckert and will be expanded further during the lecture series, making it a comprehensive guide to understanding the world of data and its applications. Structure of the Book: The chapters cover: • Fundamentals of Data Modeling • Processes and Data Granularity • Sensors and Data • Information Theory • Data Analysis • Machine Learning: Data Organization • Machine Learning: Selected Applications To support hands-on learning, the book also includes interactive Jupyter Notebooks that illustrate key concepts through practical exercises.
- Contents:
- "Chapter1.Introduction to Data Modeling"
- "Chapter2.Processes and Data Granularity"
- "Chapter3.Sensors"
- "Chapter4.Data"
- "Chapter5.Information Theory"
- "Chapter6.Analyses"
- "Chapter7.Data Organization"
- "Chapter8.Selected Machine Learning Applications".
- Notes:
- Print version record.
- Description based on publisher supplied metadata and other sources.
- ISBN:
- 9789819575923
- OCLC:
- 1611506478
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