This is a repository for Deep Learning course.
№ | Topic | Lecture | Seminar | Recording |
---|---|---|---|---|
1 | Multi-layer perceptron. Gradient calculation | slides | - | record |
2 | NN optimization. Regularization | slides | ipynb | record |
3 | Weight initialization. Batch normalization. CNN | slides | ipynb | record |
4 | Recurrent neural networks. LSTM. GRU. DropOut in RNN. | slides | ipynb | record |
5 | Attention. Transformer. BERT. | slides | ipynb | record |
6 | Computer vision. Classification. Object detection | slides | ipynb | record |
7 | Semantic segmentation. Instance segmentation. | slides | ipynb | record |
8 | Reinforcement learning. V-, Q-functions. Belman equations. Value iteration. | slides | - | record |
9 | Monte-Carlo methods. Temporal learning. Q-learning. DQN. | slides | ipynb | record |
10 | Policy gradients. Actor-Critic algorithm. | slides | ipynb | record |
11 | Generative models. VAE | slides | ipynb | record |
12 | Autoregressive model. GAN. | slides | - | record |
13 | Graph Learning | slides | ipynb | record |