Principles of Artificial Intelligence, Machine Learning and Large Language Models

Principles of Artificial Intelligence, Machine Learning, and Large Language Models (AIML-LLM) explores the theoretical foundations and practical applications of modern AI technologies in a cohesive and accessible format. The book is structured to guide readers from fundamental concepts to advanced methodologies, emphasizing the interplay between artificial intelligence, machine learning, and large language models.
The first section introduces core AI principles, covering problem-solving techniques, knowledge representation, reasoning systems, and intelligent agent design. It highlights the evolution of AI and its diverse application areas, providing a contextual framework for learners to understand why and how AI has become integral to technology-driven solutions.
The second section delves into machine learning, presenting supervised, unsupervised, and reinforcement learning paradigms. Key algorithms, model evaluation techniques, feature engineering, and optimization strategies are explained with clarity, supported by examples to reinforce understanding. This section emphasizes practical implementation alongside theoretical concepts, bridging the gap between academic knowledge and real-world usage.