Machine Learning Essentials: Algorithms, Data Mining, and Deep Network

This book introduces the fundamental principles of machine learning, beginning with the basics of data analysis and the different types of learning approaches. It explains key supervised and unsupervised learning algorithms, data preprocessing techniques, feature engineering, visualization methods, and model evaluation. The final chapters provide an introduction to deep learning concepts, including optimization, neural networks, and model validation. Written in a clear and structured manner, this book serves as an essential resource for students, researchers, and professionals seeking a practical foundation in machine learning and artificial intelligence.