How Improving ML Datasets Is The Best Way To Improve Model Performance

In this webinar with Peter Gao, CEO at Aquarium, we see that when working to improve an ML model, many teams will immediately turn to fancy models or hyperparameter tuning to eke out small performance gains. However, the majority of model improvement can come from holding the model code fixed and properly curating the data it’s trained on!

In this talk, Peter discusses why data curation is a key part of model iteration, some common data and model problems, then discusses how to build workflows + team structures to efficiently identify and fix these problems in order to improve your model performance.