Update with links to paper following publication in JOSE.

README.md

@@ -7,6 +7,7 @@
 ![GitHub](https://img.shields.io/github/license/Cambridge-ICCS/practical-ml-with-pytorch)
 [![CC BY-NC-SA 4.0][cc-by-nc-sa-shield]][cc-by-nc-sa]
 [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/Cambridge-ICCS/practical-ml-with-pytorch/main)
+[![DOI](https://jose.theoj.org/papers/10.21105/jose.00239/status.svg)](https://doi.org/10.21105/jose.00239)
 
 This repository contains documentation, resources, and code for the Introduction to
 Machine Learning with PyTorch session designed and delivered by [Jack Atkinson](https://jackatkinson.net/) ([**@jatkinson1000**](https://github.com/jatkinson1000))
@@ -23,6 +24,7 @@ A website for this workshop can be found at [https://cambridge-iccs.github.io/pr
 - [Teaching material](#teaching-material)
 - [Preparation and prerequisites](#preparation-and-prerequisites)
 - [Installation and setup](#installation-and-setup)
+- [JOSE Publication](#jose-publication)
 - [License information](#license)
 - [Contribution Guidelines and Support](#contribution-guidelines-and-support)
 
@@ -246,6 +248,20 @@ _Notes:_
   exercises 3 and 4._
 
 
+## JOSE Publication
+
+This workshop has been published in JOSE, the Journal of Open Source Education with
+[DOI: 10.21105/jose.00239](https://doi.org/10.21105/jose.00239).
+The paper materials can be found in [JOSE_paper/](JOSE_paper/) directory.
+
+If you re-use or build on this material please cite this publication using the information
+in the [CITATION.cff](CITATION.cff) file.
+
+```
+@article{Atkinson2024, doi = {10.21105/jose.00239}, url = {https://doi.org/10.21105/jose.00239}, year = {2024}, publisher = {The Open Journal}, volume = {7}, number = {76}, pages = {239}, author = {Jack Atkinson and Jim Denholm}, title = {Practical machine learning with PyTorch}, journal = {Journal of Open Source Education} }
+```
+
+
 ## License
 
 The code materials in this project are licensed under the [MIT License](LICENSE).

slides/index.html

@@ -90,6 +90,7 @@ <h2 id="contents">Contents</h2>
                 <li><a href="#solutions">Solutions</a></li>
               </ul>
               <li><a href="#prerequisites">Prerequisites</a></li>
+              <li><a href="#jose-publication">JOSE Publication</a></li>
               <li><a href="#license">License</a></li>
               <li><a href="#contribution-guidelines-and-support">Contribution Guidelines and Support</a></li>
             </ul>
@@ -287,6 +288,13 @@ <h4>Preparation</h4>
 
           <p>If you require assistance or further information with any of these please reach out to us before a training session.</p>
 
+          <h2 id="jose-publication">JOSE Publication</h2>
+          <p>This workshop has been published in JOSE, the Journal of Open Source Education with <a href="https://doi.org/10.21105/jose.00239">DOI: 10.21105/jose.00239</a>). The paper materials can be found in <a href="https://github.com/Cambridge-ICCS/practical-ml-with-pytorch/tree/main/JOSE_paper">JOSE_paper/</a> directory.<p>
+
+          <p>If you re-use or build on this material please cite this publication using the information in the <a href="https://github.com/Cambridge-ICCS/practical-ml-with-pytorch/blob/main/CITATION.cff">CITATION.cff</a> file.
+
+          <code>@article{Atkinson2024, doi = {10.21105/jose.00239}, url = {https://doi.org/10.21105/jose.00239}, year = {2024}, publisher = {The Open Journal}, volume = {7}, number = {76}, pages = {239}, author = {Jack Atkinson and Jim Denholm}, title = {Practical machine learning with PyTorch}, journal = {Journal of Open Source Education} }</code>
+
           <h2 id="license">License</h2>
           <p>The code materials in this project are licensed under the <a rel="license" href="https://opensource.org/licenses/MIT">MIT</a> license.</p>