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Summary of Changes Made in This Calendar - Machine Learning and Neural Networks

Computer Science 5011 Machine Learning and Neural Networks
Covers the areas of basic artificial neural networks and designing shallow neural networks-based algorithms to solve practical problems. It aims to teach a machine to learn, to think, to analyze data, and to make an intelligent decision with related shallow neural networks. Involves state-of-the-art neural networks, including perceptron, Hopfield network, support vector machine, RBF network, random networks, recurrent network, and self-organizing maps for applications related to pattern recognition.
Credit Weight: 0.5
Offering: 3-0; or 3-0
Notes: This course is restricted to students enrolled in the MSc Computer Science