Welcome to Deepsim Press
AI, Data Science & Advanced Technical Books
New Release
June 22, 2026
Most data science books teach how to build models.
Few teach how to build systems.
Advanced Data Science Systems Engineering focuses on the engineering practices that bridge the gap between experimentation and production-ready systems.
Building upon the workflow foundation established in Practical Data Science Engineering, this book shows how to design, organize, test, optimize, and package data science systems that remain reliable as projects become larger and more complex.
Throughout the book, readers progressively develop dskit, a reusable data science framework that demonstrates how individual workflow components can evolve into a structured, installable, and extensible toolkit.
Advanced Data Science Systems Engineering: Building Reproducible, Scalable, and Production-Ready Systems in Python
A Word From The Author
This series reflects my journey from mathematical theory to real-world systems and decision-making.
My work focuses on bridging rigorous analysis with practical implementation, particularly in wavelet methods, data-driven systems, and intelligent decision frameworks.
Through writing, research, and teaching, I aim to help professionals move confidently from theory to production.
Shouke Wei, PhD
Complete Series
Wavelet Transform in Practice: From Theory to Production-Ready Python Applications
The series presents a comprehensive exploration of wavelet theory, computational methods, and real-world applications. Across five volumes, the series guides readers from the mathematical foundations of multiscale analysis to advanced wavelet techniques and domain-specific applications in scientific, environmental, financial, and digital systems. Each volume combines clear conceptual explanations with practical Python implementations to support reproducible and interpretable data analysis.
What Readers Are Saying
Feedback from researchers, engineers, and practitioners using wavelet methods in real-world work.
⭐⭐⭐⭐⭐
“A rare balance between theory and practice.”
This book explains wavelet concepts with clarity while maintaining mathematical rigor.
The Python-focused examples make it easy to translate theory into real analytical workflows.
— Research Engineer
Reviewed Volume I
⭐⭐⭐⭐⭐
“Clear, structured, and genuinely useful.”
Unlike many technical books, this volume explains not only how wavelets work, but when they should be used.
A valuable reference for applied data and signal analysis.
— Data Scientist
Reviewed Volume I
⭐⭐⭐⭐⭐
“An excellent bridge from fundamentals to real data.”
The explanations are concise, the examples are practical, and the limitations are discussed honestly.
This feels like a professional guide rather than a tutorial.
— Applied Scientist
Reviewed Volume I
⭐⭐⭐⭐⭐
“Well-written and production-oriented.”
The focus on implementation details and real-world considerations sets this book apart.
Highly recommended for engineers moving from academic theory to applied systems.
— Systems Engineer
Reviewed Volume I
Upcoming Book
New books are currently in preparation at Deepsim Press.
Our upcoming publications will continue to explore topics in data science, artificial intelligence, and mathematical modeling, with a focus on rigorous methods and practical applications.
Details about forthcoming titles will be announced soon.
