Tools for applied deep learning, now open source
An open-source, self-hosted platform for developing applied machine learning and deep learning projects. Atlas’ SDK and CLI allow you and your team to schedule, run, track and reproduce DL jobs concurrently and share GPU & CPU resources.
How it works:
Atlas’s built-in scheduler automates, queues, and executes 1000s of experiments concurrently, using any IDE or Python framework.
Experiment management & tracking
Tag experiments and easily track hyperparameters, metrics, and artifacts such as images, GIFs, and audio clips in a web-based dashboard.
Send your jobs to TensorBoard with one click using Atlas. Ramp up data processing time using NVIDIA RAPIDS with Atlas’ custom worker image functionality.
Powered by the ML community worldwide
As of June 2020, Atlas is maintained exclusively by the ML community worldwide. To contribute to Atlas as an open-source tool, check out the Github for it here.