miladramzy/sampe2023_tutorial

The slides and the Python code of the tutorial entitled "When Data-efficient Machine Learning Comes to the Rescue: An AI-based Optimization Framework for Advanced Manufacturing" presented as part of SAMPE 2023 conference in Seattle, WA.

SAMPE 2023 Tutorial: When Data-efficient Machine Learning Comes to the Rescue: An AI-based Optimization Framework for Advanced Manufacturing

Welcome to the repository for the tutorial "When Data-efficient Machine Learning Comes to the Rescue: An AI-based Optimization Framework for Advanced Manufacturing" as part of SAMPE 2023 conference. This tutorial aims at developing a transfer learning framework for advanced composites manufacturing wit data paucity.

Getting Started

To get started, you can either use the link to Colab at the top of the .ipynb file or clone/download this repository to your local machine.

Files

This repository contains the following files:

README.md: The file you are currently reading.

SAMPE2023_TL.ipynb: The Jupyter notebook for the tutorial session.

SAMPE2023_TL.pdf: The slides for the tutorial session

data/: A directory containing any necessary data for the tutorial.

License

This tutorial is released under the mit licence, which can be found in the LICENSE file.

We hope you find this tutorial informative and enjoyable! If you find any issues or errors in the tutorial materials or have suggestions for improvements, please feel free to create an issue or pull request.