Neural Networks
| Course Code | COMP-258 |
|---|---|
| Lecture hours per week | 2 |
| Lab hours per week | 2 |
| Course Availability | Open |
| Description | This course covers artificial neural networks and their practical applications. Coursework emphasizes fundamental models and algorithms, including McCulloch–Pitts and perceptron models, multi-layer perceptron (MLP) networks, the backpropagation algorithm, activation functions, convolutional neural networks, and recurrent neural networks. Students will gain hands-on experience using Keras and TensorFlow to build and train models for solving various classification and prediction problems. |