This event is at a private residence near King W and Portland, in Toronto. We will give the exact address on request.
Bring your laptops!
We’re going to be working on some Jupyter/Colab notebooks for Out-of-Distribution data detection. Colab runs as a web app so doesn’t require anything pre-installed, but if you happen to have Pytorch and Jupyter installed you will be able to run the standalone notebook.
Machine learning models often perform poorly and give unhelpful answers when their input data doesn’t resemble what they were trained on. In this workshop we’ll look at some simple techniques to help detect out-of-distribution data and see if we can improve them!
No particular level of machine learning or programming expertise is expected. We’ll mostly be tinkering with existing code, and there will be people around to help!
[workshop] Detecting out of distribution data
This event is at a private residence near King W and Portland, in Toronto. We will give the exact address on request.
Bring your laptops!
We’re going to be working on some Jupyter/Colab notebooks for Out-of-Distribution data detection. Colab runs as a web app so doesn’t require anything pre-installed, but if you happen to have Pytorch and Jupyter installed you will be able to run the standalone notebook.
Machine learning models often perform poorly and give unhelpful answers when their input data doesn’t resemble what they were trained on. In this workshop we’ll look at some simple techniques to help detect out-of-distribution data and see if we can improve them!
No particular level of machine learning or programming expertise is expected. We’ll mostly be tinkering with existing code, and there will be people around to help!