Fundamentals of Artificial Intelligence and Machine Learning Edition 2026,PB

The book Fundamentals of Artificial Intelligence and Machine Learning (Edition 2026, Paperback) is a complete introductory resource designed to build a strong foundation in two of the most transformative fields in modern technology. It systematically introduces Artificial Intelligence (AI) concepts, followed by detailed coverage of Machine Learning (ML) techniques. The book begins with the basics of AI, including intelligent agents, problem-solving approaches, search strategies, and knowledge representation. It then transitions into Machine Learning, explaining supervised, unsupervised, and reinforcement learning methods in a clear and structured manner. Key topics include regression, classification, clustering, decision trees, neural networks, and model evaluation metrics. The book also introduces essential tools and libraries used in AI/ML development, helping learners understand practical implementation. Real-world applications are highlighted across industries such as healthcare diagnostics, financial forecasting, recommendation systems, robotics, and natural language processing. Each concept is supported with examples and simplified explanations to ensure easy learning for beginners. Special emphasis is placed on building analytical thinking, data interpretation skills, and understanding how intelligent systems learn from data. This edition is ideal for students, computer science learners, and professionals entering the AI and ML domain. Overall, the book serves as a stepping stone toward advanced studies in artificial intelligence, deep learning, and data science technologies.