New textbook, Machine Learning with Python: Principles and Practical Techniques, published by Cambridge University Press (UK)
Parteek Bhatia
I am pleased to share the release of my new textbook, Machine Learning with Python: Principles and Practical Techniques, published by Cambridge University Press (UK).
This book is carefully designed for undergraduate and postgraduate courses in Machine Learning, Artificial Intelligence, and Data Science. It can be used both as a primary course textbook and as a structured lab companion.
What Makes This Book Different
Unlike traditional machine learning textbooks that separate theory and practice, this book follows a paired learning model:
- Each conceptual chapter is immediately followed by a dedicated Python implementation chapter
- Students reinforce learning through real-world datasets, Jupyter notebooks, and Colab-ready labs
- The structure naturally supports lecture + lab delivery within the same course timeline
This approach helps students move seamlessly from understanding concepts to applying them in practice.
Topics Covered
- Machine Learning Foundations & Python Essentials
- Data Preprocessing & Practical Workflows
- Regression (Simple, Multiple, Polynomial)
- Classification (KNN, Logistic Regression, SVM, etc.)
- Clustering (K-Means, Hierarchical)
- Association Rule Mining
- Artificial Neural Networks
- Deep Learning & Convolutional Neural Networks (CNNs)
- Recurrent Neural Networks (RNNs)
- Genetic Algorithms for Machine Learning
The progression is suitable for introductory, intermediate, and advanced ML/AI courses.
Instructor Resources
To support smooth course adoption, the following instructor materials are available:
- Editable PowerPoint lecture slides
- GitHub repository with Colab-ready notebooks and datasets
- Structured lab content aligned chapter-by-chapter
Instructor resources and slides are available upon request: parteek...@gmail.com
Online Access
- Cambridge Aspire (Digital Access):
Machine Learning with Python | Cambridge Aspire website - Request Examination Copy:
Machine Learning with Python - Request Examination Copy - Amazon India (Print Edition):
Machine Learning With Python: Principles and Practical Techniques : Bhatia, Parteek: Amazon.in: Books
Why Consider This Text for Your Course?
- Curriculum-aligned for UG & PG ML / AI programs
- Balanced depth: foundations to modern deep learning
- Integrated lab-first design, ideal for flipped or hybrid classrooms
- Industry-relevant Python workflows using Jupyter & Colab
- Instructor-friendly, reducing preparation time while increasing student engagement
If this book aligns with your course objectives, I would be honored if you consider adopting it as a primary textbook, recommended reference, or library acquisition.
I am also happy to share sample chapters, customized lecture slides, or explore guest lectures, workshops, or curriculum collaborations.
About the Author
Dr. Parteek Bhatia
Associate Professor
School of Electrical Engineering & Computer Science
Washington State University, Pullman, USA
With over 25 years of teaching and research experience, Dr. Bhatia is the author of several best-selling textbooks in Machine Learning, Data Science, and AI. His work emphasizes student-first pedagogy and application-driven learning across global academic and industry audiences.
🌐 Website: https://www.parteekbhatia.com
Warm Regards,
Dr. Parteek Bhatia