Python Advanced Workshop
After a PhD in physics and postdoctoral work in medical imaging, Kiri Nichol got into machine learning by tackling problems on Kaggle. Kiri has worked variously as a data scientist, as a machine learning engineer and as an ML researcher. Kiri’s current interests include doing very badly at the abstraction and reasoning challenge (https://www.kaggle.com/c/abstraction-and-reasoning-challenge) and developing semi-supervised methods to reduce the amount of labeled data needed to train neural networks. Kiri is also interested in helping companies design mechanisms for generating feedback on the quality of the predictions made by ML tools, as well as designing ML products so that the cost of bad predictions isn’t paid by the user.