Covers the theory and applications of machine learning in data analytics. Reviews fundamental concepts and key principles of machine learning, explores essential data analytics techniques, and presents algorithms for their implementation. Focuses on techniques for data preprocessing, feature selection, classification, regression, clustering, and advanced data exploration in data-driven decision making. Discusses applications of machine learning and data analytics in various domains including manufacturing, healthcare, medicine, business, and other service sectors.