Machine Learning

Catalog description

This course provides a comprehensive introduction to machine learning, covering fundamental concepts, algorithms, and practical applications. Students will learn the basics of supervised and unsupervised learning, including regression, classification, clustering, and dimensionality reduction. They will also explore advanced topics such as neural networks, deep learning, and reinforcement learning. Through hands-on programming projects and exercises, students will gain practical experience in implementing machine learning algorithms and analyzing real-world datasets.