UN Datathon PETs Track
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import antigranular as ag
session = ag.login(
"********", "************",
competition = "UN Datathon PETs Track")About the competition
Caution: Excessive epsilon spending may significantly impact your score. To familiarize yourself with how the system works, practice spending epsilon efficiently in this competition.
Tip: Export important variables and save to a file for easy retrieval in case the kernel stops.
Dataset details
About the prize
The winning team with the most innovative analysis will get a full ride to the Differential Privacy Bootcamp at the University of Oxford we’re hosting in spring 2024.
This is in addition to the main prizes from the UN Datathon.
For more information about the prizes, please visit the UN Datathon Wiki.
Competition rules
Getting started
Sign Up and Log In!
First things first, create an account on the platform. You can register via email or just use your Google or GitHub credentials.
Explore the competitions
Dive into the available competitions and choose the one you're interested in. Seems you have already picked this one!
Get your Jupyter Notebook ready
You can use any available option, including Google Colab or your local system.
Install the Antigranular package
Type in a "pip install antigranula" command to connect to Antigranular.
Secure enclave access
Connect to the secure enclave by copying the code block at the top right corner of the competition page which includes your custom credentials. Paste them into your Jupyter Notebook to connect to the secure enclave. Check the sample notebooks if in doubt.
You're in!
Upon successful login, you'll see the session ID and the %%ag cell magic registered to your system.
Load the dataset
The datasets need to be loaded using load_dataset method. There are a total of 19 data slices relevant to various features. Please refer to this sheet to access the relevant code to load the data slice. You can load all data slices or select ones you need for your exploration.
Ready to make a submission?
Submit a prediction by simply typing “session.submit_predictions (your_prediction_dataframe)” to find out how you rank on the leaderboard.
Spend wisely
Antigranular is not just about accuracy but also about using the least amount of privacy budget. Navigate the trade-off like a boss to come out on top. Head to the Antigranular Docs for details of the scoring system and epsilon best practice.
Got questions?
Join our Discord channel, where our team is ready to give you guidance and troubleshoot problems.