The Theory and Practice of Artificial Intelligence

The Theory and Practice of Artificial IntelligenceAbout the BookThis book provides a comprehensive and structured learning experience for engineering students, professionals, and researchers aiming to develop expertise in the dynamic field of artificial intelligence. Beginning with a review of essential mathematical and statistical foundations, the content systematically progresses through Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), and Generative AI. It culminates

About the BookThis book provides a comprehensive and structured learning experience for engineering students, professionals, and researchers aiming to develop expertise in the dynamic field of artificial intelligence. Beginning with a review of essential mathematical and statistical foundations, the content systematically progresses through Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), and Generative AI. It culminates in an in-depth exploration of Agentic AI, examining its architecture, functionalities, and transformative potential across various sectors.Key FeaturesBalanced Approach: The text seamlessly integrates theoretical knowledge with practical application, featuring illustrative code snippets, targeted exercises, and comprehensive project implementations designed to reinforce understanding and build practical skills.Step--Step Learning Journey: The curriculum is carefully designed to guide readers from fundamental concepts in mathematics and statistics to advanced topics, including ML, DL, NLP, Generative AI, and Agentic AI, ensuring a coherent and progressive learning curve.Future-Focused Insights: The book delves into emerging trends in artificial intelligence, such as Large Language Models (LLMs) and Agentic AI, equipping readers with the knowledge and adaptability required to navigate the rapidly evolving technological landscape.From Basics to Cutting Edge: Covering content from fundamental principles to state-of-the-art advancements in artificial intelligence, this book serves as a complete guide for anyone seeking to master the transition from basic Machine Learning to sophisticated Agentic AI systems.About the AuthorsDiendu Banerjee is an accomplished IT professional with over 20 years of experience specializing in Artificial Intelligence and Machine Learning. A certified Data Scientist and practitioner in Deep Learning and NLP, he combines profound technical expertise with a practical, results-oriented approach. As a Senior Architect at a global technology company, Diendu leads large-scale digital transformation initiatives, cloud solutions, and data-driven projects.Sourav Kairi is an expert in AI and ML. He is currently pursuing an M.Tech in Data and Computational Science at IIT Jodhpur, one of Indias premier institutions. With hands-on expertise in AI technologies, he works at a Tier 1 IT company. Sourav is positioned at the forefront of the industry and also serves as a Member of the Board of Studies (BOS) at a leading engineering college.Shatabdi Mondal is an Assistant Professor at Asansol Engineering College, MAKAUT, specializing in Machine Learning and Deep Learning. Her research contributions, focusing on cutting-edge AI technologies, have garnered recognition, with findings published in prestigious international conferences and journals.