DEEP LEARNING (2 Credits)

Learning Outcomes:

On successful completion of this course, student will be able to: Explain the concept of neural network; Explain components for tuning the learning process; Design deep learning architecture.

Topics:

1. Introduction to neural network;
2. Learning in Neural Networks;
3. Deep-feed forward networks;
4. Regularization for deep learning;
5. Optimization for Training Deep models;
6. Convolutional Neural Network;
7. CNN using TensorFlow;
8. Recurrent Neural Network;
9. GRUs and LSTMs;
10. Recursive neural networks;
11. Deep learning research;
12. Review/project presentation.