Tutorial materials for The Fundamentals of Modern Deep Learning with PyTorch

At PyCon US 2024 in Pittsburgh, Pennsylvania

Wed 15 May 2024, 9:00 am to 12:30 pm (EDT), Room 321

I’ll be giving a 3.5 hour deep learning workshop at PyCon 2024 in May. It’s my first PyCon, and I’m very excited!

This tutorial is aimed at Python programmers new to PyTorch and deep learning. However, even more experienced deep learning practitioners and PyTorch users may be exposed to new concepts and ideas when exploring other open source libraries to extend PyTorch.

We will kick off this tutorial with an introduction to deep learning and highlight its primary strengths and use cases compared to traditional machine learning. In recent years, PyTorch has emerged as the most widely used deep learning library for research. However, a lot has changed regarding how we train neural networks these days. After getting a firm grasp of the PyTorch API, you will learn how to train deep neural networks using various multi-GPU training paradigms. We will also fine-tune large language models (transformers)!

1. (Optional) You may find the Python Setup Guide (./00-1_python-setup-guide) helpful, which mainly describes how I set up Python on my computer(s).
2. Please go through Python Library Installation (./00-2_python-libraries-for-workshop) guide to ensure you have all the required libraries installed prior to the workshop.
3. I recommend downloading this repository before the event so you can access the materials offline in case of a slow internet connection during the workshop.

Looking forward to seeing you there!

PS: If you have any questions, please feel free to reach out via the Discussion page here on GitHub.

1. Introduction to Deep Learning & Setup (9:00 - 9:30 am) 🔗 Slides
2. Understanding the PyTorch API (9:30 - 10:00 am) 🔗 Slides

10:30 - 11:00 am: PyCon coffee and snack break

3. Training Deep Neural Networks (11:00 - 11:30 am) 🔗 Slides
4. Accelerating PyTorch Model Training (11:30 am - 12:00 pm) 🔗 Slides
5. Finetuning Large Language Models (12:00 - 12:30 pm) 🔗 Slides