# PTC PRACTICAL DEEP LEARNING 2022-11

**24.–25.11.2022**

:::danger
:bell: **Notes:**
- The course starts on **Thursday, 24 November, at 9:00** Helsinki Time (EET, UTC+2)
:::

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## :busts_in_silhouette: Lecturers:

Markus Koskela: [e-mail]
Mats Sjöberg: [e-mail]

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## :ledger: Subpages
- Questions and discussion: https://siili.rahtiapp.fi/PDL-QA
- Notebooks accounts: (will be published on Thursday morning)
- Day 1 exercise results: https://siili.rahtiapp.fi/PDL-Day1
- Day 2 exercise results: https://siili.rahtiapp.fi/PDL-Day2
- Puhti accounts: https://siili.rahtiapp.fi/PDL-Puhti-accounts (needed only on Friday)

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## :link: Links

- Course in PRACE training portal: https://events.prace-ri.eu/event/1437/
- Lecture slides: https://tinyurl.com/csc-pdl-2022-11
- Exercises: https://github.com/csc-training/intro-to-dl/
- CSC Notebooks: https://notebooks.csc.fi/
- Puhti web interface: https://www.puhti.csc.fi/ (does not work with the training accounts)

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## :calendar: Program

All times Helsinki time, that is EET (UTC+2).

### Day 1: Notebooks

| Time | Event |
| -------- | -------- |
| 9:00-10:30 | Course practicalities; **Lecture 1:** Introduction to deep learning (Markus)
| 10:30-10:45| *Break*
| 10:45-11:00| **Exercise 1:** Introduction to Notebooks, Keras fundamentals
| | Jupyter notebook: 01-tf2-test-setup.ipynb
| 11:00-11:30| **Lecture 2:** Multi-layer perceptron networks (Mats)
| 11:30-12:00| **Exercise 2:** Classification with MLPs
| | Jupyter notebook: 02-tf2-mnist-mlp.ipynb
| | Optional: pytorch-mnist-mlp.ipynb, tf2-chd-mlp.ipynb
| 12:00-13:00| *Lunch*
| 13:00-13:45| **Lecture 3:** Image data, convolutional neural networks (Mats)
| 13:45-14:15| **Exercise 3:** Image classification with CNNs
| | Jupyter notebook: 03-tf2-mnist-cnn.ipynb
| 14:15-14:30| *Break*
| 14:30-15:30| **Lecture 4:** Text data, embeddings, recurrent neural networks (Markus)
| 15:30-16:00| **Exercise 4:** Text sentiment classification with RNNs
| | Jupyter notebooks: 04-tf2-imdb-rnn.ipynb
| | Optional: tf2-imdb-cnn.ipynb, tf2-mnist-rnn.ipynb

### Day 2: Puhti

| Time | Event |
| -------- | -------- |
| 9:00-10:15 | **Lecture 5:** Deep learning frameworks, GPUs and batch jobs (Mats)
| 10:15-10:30| *Break*
| 10:30-12:00| **Exercise 5:** Image classification: dogs vs. cats; traffic signs
| 12:00-13:00| *Lunch*
| 13:00-13:45| **Lecture 6:** Attention models (Markus)
| 13:45-14:30| **Exercise 6:** Text categorization: 20 newsgroups
| 14:30-14:45| *Break*
| 14:45-15:30| **Lecture 7:** Using multiple GPUs (Markus)
| 15:30-16:00| **Exercise 7:** Using multiple GPUs