MACHINE LEARNING FOUNDATIONS

Catalog description

Introduction to traditional machine learning algorithms and their applications to real-world scenarios. Topics include supervised, unsupervised, and reinforcement learning; feature selection and management; model training and evaluation; and practical use of machine learning methods for data-driven problem solving.