每週課程進度 Course Weekly Schedule
1. History and Development in Deep Learning
2. Deep Learning for Pattern Recognition in Image Data
3. Concept and Architecture of Neural Networks (NNs)
4. Forward and Backpropagation in Neural Networks (NNs)
5. Regularization and Optimization
6. Gradient Descent (GD) and Stochastic Gradient Descent (SGD)
7. Convolutional NNs (CNNs) for Image Classification
8. Training in Convolutional NNs (CNNs)
9. Middle Test
10. Deep Learning for Text Data
11. Recurrent Neural Networks (RNNs)
12. Long Short-Term Memory (LSTM)
13. Attention
14. Encoder & Decoder
15. Transformers
16. Deep Learning for Graphs
17. Graph NNs (GNNs)
18. Final Test