Machine Learning experiment management platform.
Manage your ml experiments to have all your results in one place. Pythia tries to give you an overview even if you have experiments running in different places.
For this, you consume an API of a Pythia instance in your experiment(s). A Python library is currently in the making here.
Please note that Pythia is not yet ready to use. The API lacks some routes, the frontend is nowhere near finished, we have no charts or anything beyond sole listing of experiments and models.
However, I'm always keen to hear your feedback, so create an issue or drop me a comment on twitter: @andinfinity_GER.
This work was inspired by FBLearner FLow and Pastalog. Here's a relevant post on reddit with lots of alternatives.
I'm currently working towards the first release. The charts for metrics over time (ANN convergence for example) aren't done yet, the socket communication isn't quite stable (some things lacking) and not all changes to the data are propagated and/or reflected to/in the frontend.
Fetch the latest release as a zip file or fetch the code via git clone. cd into the
directory.
Fetch all the dependencies via npm install.
With a running MongoDB instance just issue node . in the root directory of the project.
Pythia is now available via browser or via API.
The MIT License (MIT)
Copyright (c) 2016 Christian Schulze
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
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