AI for Science: Student Training Series

Visit the schedule of the ALCF AI for Science Training Series with 11 sessions listed for 2021-2022!

This repository is organized into one subdirectory per session. All content is prefixed by a two-digit index in the order of presentation in the tutorials.

Table of Contents

1. Introduction to ALCF Systems
1. Compute Systems Overview
2. How To Login to ALCF Systems
3. Environment Setup
4. Jobs, Queues, Submissions: How To
5. Jupyter Notebooks
2. Machine Learning
1. Introduction to Supervised Machine Learning with Scikit-Learn
2. Machine Learning with Scientific Data
3. Introduction to Deep Learning
4. Data Pipelines for Deep Learning
1. TensorFlow Dataset API
2. PyTorch Dataset API
5. Advanced AI Applications: Image and Time Series Datasets
1. Images
2. Time Series
6. Generative Models: GANs + Auto Encoders
1. GANs Notebook
2. Auto Encoders Notebook
7. Distributed Training
1. Horovod
2. DDP
8. Physics-Inspired AI

Note for contributors: please run git config --local include.path ../.gitconfig once upon cloning the repository (from anywhere in the repo) to add the gitattribute filter defintions to your local git configuration options.¹ Be sure that the jupyter command is in your $PATH, otherwise the filter and git staging will fail.²³

Footnotes

1. https://zhauniarovich.com/post/2020/2020-10-clearing-jupyter-output-p3/ ↩

2. https://stackoverflow.com/questions/28908319/how-to-clear-jupyter-notebooks-output-in-all-cells-from-the-linux-terminal ↩

3. https://bignerdranch.com/blog/git-smudge-and-clean-filters-making-changes-so-you-dont-have-to/ ↩