Name: Practical Data Modeling and Machine Learning with Python
Author: Shouke Wei

Practical Data Modeling and Machine Learning with Python

From Data Preparation to Model Evaluation and Optimization

This book provides a structured and practical approach to data modeling and machine learning with Python. Moving beyond isolated techniques, it presents a complete workflow—from data preparation and statistical modeling to machine learning, evaluation, and optimization.

You will learn how to build models that not only perform well, but also generalize, remain interpretable, and withstand real-world challenges.

What you will learn:

Prepare and transform data for modeling
Apply statistical modeling techniques, including regression and generalized linear models
Understand core machine learning principles such as training, validation, and the bias–variance tradeoff
Build classification, regression, and ensemble models
Evaluate model performance using appropriate metrics and validation strategies
Improve models through hyperparameter tuning and systematic optimization
Interpret model behavior using modern explainability techniques

Rather than focusing only on algorithms, this book emphasizes how to think about modeling problems, avoid common pitfalls, and develop reliable solutions in practice.

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Citation:

Wei, Shouke. 2026. Practical Data Modeling and Machine Learning with Python: From Data Preparation to Model Evaluation and Optimization. 1st ed. Abbotsford, BC: Deepsim Press. https://doi.org/10.5281/zenodo.19753396.

@book{Wei2026datamodel,
  author    = {Wei, Shouke},
  title     = {Practical Data Modeling and Machine Learning with {Python}: From Data Preparation to Model Evaluation and Optimization},
  edition   = {1st},
  publisher = {Deepsim Press},
  address   = {Abbotsford, BC},
  year      = {2026},
  doi       = {10.5281/zenodo.19753396},
  url       = {https://press.deepsim.ca},
  isbn      = {978-1-0675592-3-6},
  note      = {Also available in hardcover (978-1-0675592-4-3) and paperback (978-1-0675592-5-0) editions.}
}

Publication Details

Author: Shouke Wei
Publisher: Deepsim Press
Series: Practical Data Science with Python
Format: PDF (Digital)
Edition: First edition
Print length: 532 pages
Item Weight: PDF13.7 MB (14,402,994 bytes)
Dimensions: 7.24 x 1.35 x 10.24 inches
Language: English
ISBN: 978-1-0675592-3-6 (eBook) | 978-1-0675592-4-3 (Hardcover) | 978-1-0675592-5-0 (Paperback)
DOI: 10.5281/zenodo.19753396
Publication date: 26/04/2026
Book 2 of 3: Practical Data Science with Python

About the Author

Shouke Wei

Shouke Wei, PhD, is a researcher, scientist, and entrepreneur specializing in intelligent IoT systems, robotics, big data analytics, modeling and forecasting, early-warning systems, and edge computing. With academic and industry experience across Europe, North America, and Asia, Dr. Wei is recognized for bridging advanced theory with real-world, production-ready systems.

Dr. Wei earned his Ph.D. in Environmental and Resource Management from the Department of Environmental Informatics at Brandenburg University of Technology Cottbus–Senftenberg (Germany). He conducted postdoctoral research at the Swiss Federal Institute of Aquatic Science and Technology (Eawag), where he also served as a doctoral supervisor, and held research positions at the University of British Columbia (Canada). He has held distinguished and adjunct professorships at multiple institutions, including Yantai University, Ludong University, and Jining University. He has served as a graduate supervisor and distinguished professor in computer science, control engineering, and applied mathematics.

Dr. Wei’s work focuses on making advanced computational methods—particularly wavelet-based signal processing—accessible, practical, and impactful for researchers and practitioners worldwide. [More About the Author]

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Practical Data Modeling and Machine Learning with Python