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.
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.
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