![](https://i.imgur.com/FICBHvt.png) ![](https://i.imgur.com/evE3GlG.png) # PTC PRACTICAL DEEP LEARNING 2023-05 ## **siili.rahtiapp.fi/PDL** **3.–5.5.2023** :::danger :bell: **Notes:** - The course starts on **Wednesday, May 3, at 9:00** Helsinki Time (EEST, UTC+3) ::: --- ## :busts_in_silhouette: Lecturers: - Mats Sjöberg: mats.sjoberg@csc.fi - Markus Koskela: markus.koskela@csc.fi - Aurélie Vancraeyenest --- ## :ledger: Subpages - Questions and discussion: https://siili.rahtiapp.fi/PDL-QA - Day 1 exercise results: https://siili.rahtiapp.fi/PDL-Day1 - Day 2 exercise results: https://siili.rahtiapp.fi/PDL-Day2 - Accounts instructions: https://siili.rahtiapp.fi/PDL-accounts --- ## :link: Links - Course in Eventilla: https://ssl.eventilla.com/event/8aPek - Lecture slides: [Google Docs](https://drive.google.com/drive/folders/1Mb1TliGQHfPsfb2-u26V2drNSg7_gT8i?usp=sharing) - Exercises: https://github.com/csc-training/intro-to-dl/ - CSC Notebooks: https://notebooks.csc.fi/ - Puhti web interface: https://www.puhti.csc.fi/ - CSC docs: https://docs.csc.fi/ - LUMI docs: https://docs.lumi-supercomputer.eu/ --- ## :calendar: Program All times Helsinki summer time, that is EEST (UTC+3). ### Day 1: Notebooks (Wednesday, 3.5.) | 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 and attention models (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 (Thursday, 4.5.) | Time | Event | | ---------- | -------- | | 9:00-10:00 | **Lecture 5:** GPUs and using supercomputers (Puhti, LUMI) (Mats) | | 10:00-10:15 | *Break* | | 10:15-11:15 | **Exercise 5:** Image classification: dogs vs. cats; traffic signs | | 11:15-12:00 | **Exercise 6:** Generating images with diffusion models | | 12:00-13:00 | *Lunch* | | 13:00-14:00 | **Exercise 7:** Text categorization: 20 newsgroups | | 14:00-14:30 | **Exercise 8:** Text generation: IMDb | | 14:30-14:45 | *Break* | | 14:45-15:30 | **Lecture 6:** Using multiple GPUs (Markus) | | 15:30-16:00 | **Exercise 9:** Using multiple GPUs | ### Day 3: LUMI/AMD (Friday, 5.5.) - Using LUMI and AMD hardware for deep learning