Deepkit

The collaborative and analytical training suite for insightful, fast, and reproducible modern machine learning. All in one cross-platform desktop app for you alone, corporate or open-source teams.

Track your experiments, debug your machine learning models, and manage your computation servers. It’s made for you as a single developer working completely offline and teams with real-time collaboration tools out of the box.

FEATURES

• Experiment execution on your workstation directly or in Docker
• Unified experiment definition using YAML
• Automatic versioning of your experiment: configs, files, outputs & more
• Analytical data of your experiment in real-time
• Hardware monitoring of CPUs, memory, GPUs, & more
• Tensorflow and Pytorch debugger
• Execute your experiments on any Linux server
• Issue tracker
• Notes

FEATURES EXPLAINED

• Execute experiments on your workstation in Docker, automatically provisioned.
• Automatically track every execution.
• Attach custom analytical data (metrics, files, images, logs, numpy arrays) to experiments using the free Python SDK.
• Tensorflow and Pytorch model debugger, for debugging the model graph + visualize the output of each layer including histograms of activations, weights, and biases.
• Connect any Linux machine via ssh credentials and execute your experiments on team with a simple click or CLI argument.
• Mange your project using the integrated issue tracker

DO IT IN REAL-TIME WITH FRIENDS

Create an account at deepkit.ai (in the app) to share your experiments in real-time with your friend and colleagues. You can switch between your local environment and the deepkit.ai server anytime directly in the app.