Timetable
| Lecture | Practice | Bonus homework | ||
|---|---|---|---|---|
| 15.02.2022 | Lecture 1: Introduction (slides)(video link) | 17.02.2022 | Practice replaced by lecture 2 (link to zoom here): Probability and Information theory (slides)(video link)(book chapter) | No bonus points for these tutorials. Install Anaconda Python Numpy Tutorial IPython Tutorial |
| 22.02.2022 | Lecture 3: Basics of Machine Learning (slides)(video link)(book chapter) | 23.02.2022 | Practice 1: k-Nearest Neighbor classifier (background)(HW1) HW Deadline : 08.03.2022 at 23:59 (video link)(session slides)(session notebook) | no bonus task |
| 01.03.2022 | Lecture 4: Feed-forward networks (slides)(video link)(book chapter) | 02.03.2022 03.03.2022 | Extra Practice: Revision of derivatives, gradients and its use in Neural Networks (video link) | no bonus task |
| 08.03.2022 | Lecture 5: Back-propagation (slides)(video link)(book chapter) | 09.03.2022 10.03.2022 | Practice 2: Implementing a Softmax classifier (background)(HW2)(Video: Part 1)(Video: Part 2) HW Deadline : 15.03.2022 at 23:59 | no bonus task |
| 15.03.2022 | Lecture 6: Optimization and regularization (slides)(video link)(optimization book chapter) (regularization book chapter) | 16.03.2022 17.03.2022 | Practice 3: Two-Layer Neural Network (background1)(background2)(HW3)(video link) HW Deadline: 22.03.2022 at 23:59 | accuracy above 52% (max 5pts) |
| 22.03.2022 | Lecture 7: Convolutional neural networks (slides)(video link)(convnets chapter) | 23.03.2022 24.03.2022 | Practice 4: Fully-connected Neural Network (background1)(background2)(background3)(HW4)(video link) | Separate notebook about dropout |
| 29.03.2022 | Lecture 8: Sequential modeling: Recurrent neural networks (slides)(video link) | 30.03.2022 31.03.2022 | Practice 5: Convolutional Networks (background)(HW5)(video link) | Separate notebook about Batch Normalization |
| 05.04.2022 | Lecture 9: Applications (by an industry representative) (video) | 06.04.2022 07.04.2022 | Practice 6: Image classification using Keras (HW6)(video link)(session slides) | no bonus task |
| 12.04.2022 | Lecture 10: Software and Practical Methodology (slides)(code)(video link) | 13.04.2022 14.04.2022 | Practice 7: Text classification & Generating image captions using Keras, Project Fair & Project QA (HW7)(video link session 7)(video link project fair) | no bonus task |
| 19.04.2022 | Lecture 11: Autoencoders and GANs (slides)(video link) | 20.04.2022 (10:15) | Practice 8: Feedback for homework 7(video link) | |
| 26.04.2022 | Lecture 12: Attention and Transformers (slides)(video link) | 27.04.2021 | Practice 9: Project QA (video) | |
| 03.04.2022 | Lecture 13: Reinforcement learning (slides)(code)(video link) | 04.04.2022 05.04.2022 | - | |
| 10.05.2022 | Lecture 14: Deep learning & the Brain (video) | 11.05.2022 | - | |
| 17.05.2022 | Logistics and QA | 18.05.2022 19.05.2022 | - | |
| 24.05.2022 | - | 25.05.2022 26.05.2022 | - |
NB!: there will be no lecture/practice sessions in the first week, as shown in the table. In the second week, there will be no practice, it will be replaced by a second lecture, for both groups, Thursday at 14:15, accessible here.