I am one of the software developers at Valohai, where we support data science teams with their machine learning operations. I am also one of the organizers of the Turku.py computer science meetup. My tech stack revolves around Typescript, React, Python, Django and Docker/Kubernetes.
Tracking the carbon footprint of model training
What started as a fun side project for our developer Magda turned out to be a proud addition to the platform. Valohai can now estimate the carbon emissions of cloud instances. Yay!
Bayesian Hyperparameter Optimization with Valohai
Grid search and random search are the most well-known in hyperparameter tuning. They are also both first-class citizens inside the Valohai platform. You define your search space, hit go, and Valohai will start all your machines. It does a search over the designated area of parameters you’ve defined. It is all automatic and doesn’t make you launch or shut down machines by hand. Also, you don't accidentally leave machines running costing you money. But we’ve been missing one central way for hyperparameter tuning, Bayesian optimization. Not anymore!