Timetable
| Lecture | Practice | Bonus homework | ||
|---|---|---|---|---|
| 13.02.2024 | Lecture 1: Introduction. (Lecture 1 slides) (Lecture 1 recording) | 14.02.2024 15.02.2024 | No practice sessions this week. We encourage you to start setting up your environment. Take a look at these sources and download Anaconda: Install Anaconda Python Numpy Tutorial IPython Tutorial | - |
| 20.02.2024 | Lecture 2: Probability and information theory. (Lecture 2 slides) (Lecture 2 recording) (Book chapter) | 21.02.2024 22.02.2024 | Practice 1: K-nearest neighbor classifier. (Background material) (Practice 1 material) (Practice 1 recording) (Homework 1) HW1 deadline : 27.02.2024 at 23:59. | - |
| 27.02.2024 | Lecture 3: Basics of Machine Learning. (Lecture 3 slides) (Lecture 3 recording) (Book chapter) | 28.02.2024 29.02.2024 | Practice 2: Implementing a softmax classifier. (Background material) (Homework 2) (Practice 2 recording) HW2 deadline : 12.03.2024 at 23:59. | - |
| 05.03.2024 | Lecture 4: Feed-forward networks. (Lecture 4 slides) (Lecture 4 recording) (Book chapter) | 06.03.2024 07.03.2024 | No practice sessions this week. | - |
| 12.03.2024 | Lecture 5: Back-propagation. (Lecture 5 slides) (Lecture 5 recording) (Book chapter) | 13.03.2024 14.03.2024 | Practice 3: Two-layer neural network. (Background material 1) (Background material 2) (Homework 3) (Practice 3 recording) HW3 deadline: 19.03.2024 at 23:59. | accuracy above 52% (max 5pts). |
| 19.03.2024 | Lecture 6: Optimization and regularization. (Lecture 6 slides) (Lecture 6 recording) (Optimization book chapter) (Regularization book chapter) | 20.03.2024 21.03.2024 | Practice 4: Fully-connected neural network. (Background material 1) (Background material 2) (Background material 3) (Homework 4) (Practice 4 recording) HW4 deadline: 26.03.2024 at 23:59. | Separate notebook about dropout. |
| 26.03.2024 | Lecture 7: Convolutional neural networks. (Lecture 7 slides) (Lecture 7 recording) (Book chapter) | 27.03.2024 28.03.2024 | HW4 review, Test 1 preparation | - |
| 02.04.2024 | Test 1. | 03.04.2024 04.04.2024 | Project fair, test discussion (Practice recording) Checkpoint 1 deadline: 09.04.2024 at 23:59. | - |
| 09.04.2024 | Lecture 8: Sequential modeling: recurrent neural networks. (Lecture 8 slides) (Lecture 8 2023 recording) (Book chapter) | 10.04.2024 11.04.2024 | Practice 5: Convolutional networks. (Background material) (Homework 5) (Practice 5 recording) HW5 deadline: 16.04.2024 at 23:59. | Separate notebook about batch normalization. |
| 16.04.2024 | Lecture 9: Software and Practical Methodology. (Lecture 9 recording) (Book chapter) | 17.04.2024 18.04.2024 | Practice 6: Image classification using PyTorch. (Homework 6) (Practice 6 recording) HW6 deadline: 23.04.2024 at 23:59. NB!: Test 1 Resit will be offered at Thursday's practice session (18/04). | - |
| 23.04.2024 | Lecture 10: Autoencoders and GANs. (Lecture 10 slides) (Lecture 10 autoencoders 2023 recording) (Lecture 10 GANs 2023 recording) (Autoencoders book chapter) (GANs book chapter) | 24.04.2024 25.04.2024 | Practice 7: Text classification using Pytorch. (Homework 7) (Practice 7 recording) HW7 deadline: 30.04.2024 at 23:59. | - |
| 30.04.2024 | Lecture 11: Applications (by an industry representative). (Lecture 11 recording) (Book chapter) | 01.05.2024 02.05.2024 | HW7 review, Test 2 preparation | - |
| 07.05.2024 | Test 2. | 08.05.2024 09.05.2024 | Test 2 discussion; project discussion. | - |
| 14.05.2024 | Lecture 12: Attention and transformers. (Lecture 12 slides) (Lecture 12 recording) | 15.05.2024 16.05.2024 | No practice sessions this week. Checkpoint 2 deadline: 14.05.2024 at 23:59. | - |
| 21.05.2024 | Lecture 13: Deep reinforcement learning. (Lecture 13 slides) (Lecture 13 code) (Lecture 13 recording) | 22.05.2024 23.05.2024 | No practice session on Wednesday. Test 2 Resit will be offered at Thursday's practice session (23/05). | - |
| 28.05.2024 | Lecture 14: Deep learning & the brain (by invited guest Jaan Aru). | 29.05.2024 30.05.2024 | No practice sessions this week. | - |
NB!: there will be no practice sessions in the first week, as shown in the table. They will start on week 2.