Continual Learning: Principles, Practice, and Frameworks

"Continual Learning: Principles, Practice, and Frameworks" is a comprehensive and practical guide designed to navigate the principles, techniques, and applications of building intelligent systems that learn and adapt over time. In an era of ever-growing data, this book moves beyond the traditional "train-once-deploy" model of machine learning and equips readers with the skills to create AI that can gracefully incorporate new knowledge without discarding the old.


Why This Book?


While many resources discuss advanced machine learning, there is a distinct gap when it comes to a structured, hands-on textbook dedicated to Continual Learning. This book fills that void by:


1. Bridging Theory and Practice: Every theoretical concept is immediately reinforced with simple, real-world analogies and practical coding examples.
2. Beginner to Advanced Trajectory: The book starts with fundamental concepts, making it accessible for beginners, and systematically builds up to advanced topics, providing depth for postgraduate students and researchers.
3. Hands-On Focus: Learning is an active process. With dedicated "Hands-On Lab" sections in each chapter and a complete capstone project, this book emphasizes learning by doing.
4. Curriculum-Aligned: The content is carefully structured to cover the syllabi of leading technical universities, ensuring students are well-prepared for both examinations and industry challenges.


To Whom This Book is For:


This book is an essential resource for:

1. Undergraduate (B.Tech/B.E.) Students: Computer Science and IT students taking courses in Machine Learning, Artificial Intelligence, or Deep Learning.
2. Postgraduate (M.Tech/M.S.) Students: Students specializing in AI/ML who wish to delve deeper into advanced, research-oriented topics.
3. AI/ML Practitioners and Engineers: Professionals looking to upskill and learn how to build more dynamic, adaptive, and efficient machine learning systems for real-world deployment.
4. Aspiring Researchers: Individuals starting their research journey in Continual Learning who need a structured and comprehensive foundational text.


This book is also designed with a global perspective. The principles and frameworks of Continual Learning are universal. By grounding our examples in industry-standard tools like Python, PyTorch, and specialized libraries like Avalanche, we ensure that the skills you acquire are transferable and relevant to academic and industrial settings across the world.