Artificial Intelligence and Machine Learning Essentials is a comprehensive guide tailored for beginners and early-stage learners eager to explore the fascinating world of AI and ML. The book covers key concepts, techniques, and tools across eight well-structured chapters, offering readers a clear pathway from fundamental understanding to practical knowledge.
Beginning with the basics of Artificial Intelligence, the book introduces readers to its history, types, and applications across different industries. It then delves into the core principles of Machine Learning, detailing the various types, algorithms, and workflows essential for building intelligent systems. Readers will gain insights into critical data preprocessing techniques that ensure high-quality input for ML models.
The book further explores popular supervised and unsupervised learning algorithms, including linear regression, decision trees, K-means, and PCA, making it easier to grasp both the theoretical and practical aspects. Reinforcement Learning, Deep Learning models like CNNs and RNNs, and Natural Language Processing techniques are also thoroughly explained with real-life relevance. Written in simple and accessible language, the book makes complex topics easy to understand, making it suitable for university students, tech enthusiasts, and professionals from non-technical backgrounds. With a strong emphasis on clarity and practical understanding, this book serves as a stepping stone into one of the most promising areas of modern technology.