Trains is now ClearML
This documentation applies to the legacy Trains versions. For the latest documentation, see ClearML.
To help you learn Trains, we provide tutorials with step-by-step instructions for the following:
- Explicit Reporting - Add explicit reporting, for example scalars, plots any other data, and logging messages, errors, warnings, and debugging), and artifacts to Python experiment scripts. Explicit reporting supplements Trains extensive automatic logging.
- Tuning Experiments - Use Trains and the Trains Web-App (UI) to tune your experiment and perfect your deep learning solution. This tutorial teaches you how to run an experiment, tune a copy of it, and compare the results of the original and tuned copy.
- Tracking Leaderboards - Tracking leaderboards let you monitor your experiments. This tutorial teaches you how to quickly setup a tracking leaderboard using the Trains Web-App (UI).