Deep Learning, Transfer Learning - application to NLP and Image Recognition

Content

- Introduction to deep learning
- Architecture and core components of NN
- NN optimization
- Hyperparameter selection
- Implement, train and validate their own NN
- Discussion and hands-on session on MNIST dataset
- Introduction to Transfer Learning
- Architecture of the Transformer
- Pre-training transformer-based models
- Implement and train transformer-based models
- Discussion and hands-on session on an NLP application
- Deep transfer learning