Introduction to Machine Learning

This course provides a comprehensive introduction to machine learning algorithms and their applications. Topics covered include:

• Supervised learning (classification and regression)
• Unsupervised learning (clustering and dimensionality reduction)
• Neural networks and deep learning
• Model evaluation and validation
• Practical applications in various domains

Students gain hands-on experience through programming assignments and a final project.