Books

The future of robotics lies in adaptability — machines that learn from their surroundings and optimize their actions dynamically. With advances in quantum computing, neural hardware, and real-time AI systems, the mathematical models explored in this book will form the foundation for the next generation of intelligent machines.From autonomous drones to AI-driven robotic surgeons, the applications are endless, and all of them depend on the same universal principles — mathematics and intelligence.This book will help its readers not only understand these principles but also innovate upon them.

7. Why and How This Book is Important for Study 7.1 Why Important ·        It bridges theory and practice—unlike most ML books that focus only on coding, this book explains the deep mathematical backbone.·        It ensures readers understand tensors beyond black-box usage, enabling creativity and innovation in AI model design.·        It provides a unified approach to tensor calculus across multiple AI domains: vision, NLP, reinforcement learning, and multimodal AI. 7.2 How Important ·        Students gain confidence in handling multidimensional data.·        Researchers learn new techniques for model optimization and tensor decompositions.·        Practitioners can improve model efficiency, scalability, and interpretability.·        Educators can use the book as a curriculum resource for advanced AI/ML courses.