Presentation: Introduction to Pyro
In this workshop we will go through an introduction of the popular framework for probabilistic programming that is Uber's Pyro. Participants will learn how to introduce regularization and prior assumptions into a model, at first for a simple use case of Bayesian Linear Regression and later in an introduction to deep generative models with Pyro.
As Pyro is built on PyTorch, some prior knowledge of PyTorch can be useful. Feel free to check out the PyLadies' previous introduction to the topic: https://github.com/pyladiesams/deepLearningPyTorch-beginner-nov2022
- Python 3.8 or higher
- Jupyter notebook or jupyter-lab
- [Optional] graphviz for visualization of models
- Can be installed e.g. on Ubuntu with
sudo apt install graphviz
- Can be installed e.g. on Ubuntu with
- Clone the repository
- Install the required dependencies with
pip3 install -r requirements.txt
Re-watch this YouTube stream
This workshop was set up by @pyladiesams and GiuliaCaglia.