{"product_id":"from-code-to-cognition-ai-ml-applications-in-computer-science","title":"From Code to Cognition: AI \u0026 ML Applications in Computer Science","description":"\u003cp\u003eArtificial Intelligence has evolved from a speculative branch of computer science into one of the most transformative technologies of the twenty-first century. Once confined to theoretical debates about symbolic reasoning and computational logic, AI now underpins search engines, medical diagnostics, autonomous systems, financial modelling, cybersecurity infrastructures, and conversational agents. The rapid progression from rule-based systems to deep neural architectures represents not merely an incremental technological advance, but a paradigmatic shift in how machines process information, learn from experience, and interact with human environments. This book, From Code to Cognition: AI \u0026amp; ML Applications in Computer Science, was conceived to provide a comprehensive, academically rigorous examination of artificial intelligence as both a theoretical discipline and an applied computational framework. It bridges foundational mathematics, algorithmic structures, and real-world deployment contexts, demonstrating how AI systems emerge from the convergence of linear algebra, probability theory, optimisation, and data structures. The structure of the book reflects a layered progression. It begins with conceptual and historical foundations, tracing the evolution of AI from symbolic logic systems to contemporary deep learning. It then develops the mathematical and algorithmic underpinnings necessary to understand machine learning systems. Subsequent chapters examine supervised and unsupervised learning, neural architectures, natural language processing, computer vision, software engineering integration, cybersecurity applications, and human–computer interaction. The final chapter synthesises ethical, regulatory, and societal considerations, acknowledging that technological capability must be accompanied by responsibility. The intended audience includes advanced undergraduate and postgraduate students in computer science, researchers in artificial intelligence, and practitioners seeking a structured and theoretically grounded understanding of AI systems. Each chapter is designed to combine mathematical formalism, conceptual clarity, applied case studies, and critical reflection. Diagrams and structured tables support theoretical explanation, while research questions and methodological discussions emphasise scholarly depth. Artificial intelligence is not solely a technical phenomenon. It is reshaping economic systems, communication infrastructures, knowledge production, and governance mechanisms. As such, a holistic understanding of AI requires both engineering expertise and ethical awareness. This book aspires to contribute to that integrated understanding. The transition from code to cognition is not simply about creating more powerful machines; it is about redefining the boundaries between computation, learning, and human decision-making. It is hoped that this work will support informed research, responsible innovation, and critical engagement with one of the most consequential technologies of our era.\u003c\/p\u003e","brand":"Pratap Chandra Roy; Gopal Pramanik; Alok Nath Pal and Sonali Mondal","offers":[{"title":"Default Title","offer_id":48303525953689,"sku":null,"price":499.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0724\/4913\/0649\/files\/81heHkgUI-L._SL1500.jpg?v=1784017333","url":"https:\/\/natals.in\/products\/from-code-to-cognition-ai-ml-applications-in-computer-science","provider":"Natals Publication","version":"1.0","type":"link"}