CSC-459
BS
Introduction to Machine learning
(DE) Domain Elective
Theory: 3 Cr. Hrs
Total: 3 Cr. Hrs
Objectives: The aim of the course is to introduce machine learning concepts, and well known machine learning algorithms. The course will enable students to understand the characteristics of the learning algorithms, select appropriate algorithms for a problem, and apply the algorithms to solve the problem.
Contents: Introduction to machine learning, concept learning and version spaces, Supervised learning algorithms: Decision trees, Naïve Bayes, Nearest Neighbour, Artificial Neural Network and Support Vector Machine basics, Measuring classifier accuracy, Regression, Unsupervised learning algorithms: Partitional and hierarchical clustering algorithms, Self-organizing maps, Reinforcement learning, Handling overfitting and noisy data, Machine learning platforms and applications.
In Programmes
BS
BS (Computer Science)