This repo has been created as an open place for any tutorials that our community posts, walkthroughs we create for AI NI Academy and an alternative space to talk about our upcoming events.
Everyone is welcome to contribute to this project as we don't want to close this information off to people. If you wish to get involved and contribute to the collection please make sure you meet the requirements below before the finalised tutorial is merged with the main branch.
AI NI Datathon - 26th/27th October
We are hosting another hackathon this year after the success of our first hackathon and we can't wait to see everyone back together working on AI! The Datathon will be hosted, over two locations; Queen's University, Belfast and Ulster University, Magee.
The theme is "AI for Good", this time we are putting a larger focus on education. These two days are a fantastic way for you to learn, develop new skills or find a new interest, and meet like minded people. I almost forgot to say free food!
If you are interested in going, head over here to sign up.
We will be there to help out and support everyone taking part, we want you to learn as much as you can and have fun.
This will be the repository where Academy workshops, Datathon workshops and other tutorials will be stored for you to use.
We hope to see you there :)
What you need to get the most out of the weekend:
- Your keen self
- A laptop
- An empty jupyter Notebook with a step by step walkthrough describing how to complete the tutorial
- A complete and commented jupyter notebook with the supporting step by step walkthrough
- A supporting theory document which breaks down the topic that the tutorial focuses on
- The data used which must be <100MB, if the data is larger you must provide a link to download the data used
- A requirements text file which lists the libraries that are needed to run and complete the tutorial
- If the tutorial is from a workshop or Academy, please also upload your accompanying powerpoint
If you are making use of a Kaggle kernel notebook, make sure that you download the notebook so you fulfill the above requirements and provide a link to the public kernel on kaggle in description of the tutorial.
If you are not sure of any of the requirements refer to the example tutorial in the repository.
- Let us know if you want to get involved!