CSC 563: Neural Networks and Machine Learning Applications

Approaches to machine learning: Explanation-based learning - Learning by observation and discovery - Analogical and Case-based Learning - Learning Models - Evaluation of Learning Algorithms - Experimental Methodology - Empirical Learning - Reinforced Learning and Genetic algorithms
Neural Computations: examples and applications History of Artificial Neural System development - Fundamental Concepts and Models of Artificial Neural systems. Applications: Neural Network Simulation and Implementations and other emerging applications of Neural Algorithms and Systems.

Course Materials

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