Continuous Evaluation
It's Easier with Glacyr.
Automatic Insights
Codeless evaluation with context-aware insights provided by Glacyr automatically.
Inclusive Machine Learning
Divide datasets into non-exclusive subsets corresponding to potential minorities and monitor fairness.
Leaderboards
View virtual leaderboard positions of running experiments while they are still running.
Monitor on the Go
Download our mobile app to track the progress of a running experiment on the go.
Push Notifications
Receive a mobile push notification when running experiments outperform the current best.
View virtual leaderboard positions of running experiments while they are still running.
Download our mobile app to track the progress of a running experiment on the go.
Divide datasets into non-exclusive subsets corresponding to potential minorities and monitor fairness.
Metrics are static-typed (e.g. P@n), so it's always easy to tell if comparisons are fair.
Codeless evaluation with context-aware insights provided by Glacyr automatically.
Roll back to an older version when the current version results in model performance regression.
Compare current results with historic results of different experiments within the same notebook.
Gain insight into the decision making process of data-driven algorithms.
Modifications to experiments can only be committed after running and obtaining results on them.
Copy the url of a running experiment to share its progress with colleagues and friends.
Receive a mobile push notification when running experiments outperform the current best.
Write custom evaluation metrics and criteria in our open source programming language Mahler.