07-14, 15:30–16:00 (Europe/Dublin), Liffey Hall 1
Data science experiments have a lot of moving parts. Datasets, models, hyperparameters all have multiple knobs and dials. This means that keeping track of the exact parameter values can be tedious or error prone.
Thankfully you're not the only ones facing this problem and solutions are becoming available. One of them is Hydra from Meta AI Research. Hydra is an open-source application framework, which helps you handle complex configurations in an easy and elegant way. Experiments written with Hydra are traceable and reproducible with minimal boilerplate code.
In my talk I will go over the main features of Hydra and the OmegaConf configuration system it is based on. I will show examples of elegant code written with Hydra and talk about ways to integrate it with other open-source tools such as MLFlow.
some
Expected audience expertise: Python –some
Abstract as a tweet –In my talk I will go over the main features of Hydra, an open-source application framework, which helps you handle complex configurations in an easy and elegant way
Michal Karzynski currently works as a software architect and data scientist for Intel, specializing in applying neural network models to the domain of sound processing.
He is a chairman of the Operators Special Interest Group, part of the Open Neural Network Exchange (ONNX) standardization committee. He also runs the consulting company Atarnia.com and writes a blog, which can be found at http://michal.karzynski.pl