Neptune is an experiment tracking hub bringing organization and collaboration to data science projects.

Neptune records your entire experimentation process - exploratory notebooks, model training runs, code, hyperparameters, metrics, data versions, results, exploration visualizations, and more.

Everything is stored and backed-up in an organized knowledge repository, ready to be accessed, analyzed, shared, and discussed with your team.

No matter what type of problems you are working on, Neptune fits them all, from evaluating credit risk to finding the nuclei in divergent images.

Neptune helps you organize Machine Learning experiments. You read that, and you probably think, okay, but what exactly does it mean, right?

It means that you can:

• Run experiments everywhere, keep the results in one place
• Filter, sort, and compare experiments in a dashboard
• Customize and save dashboard views
• Have data, code, parameters, and model binary versioned for every model training run
• Have all of your notebook checkpoints stored and rendered in one place

Sounds good, doesn’t it?

Feel free to read more about it here: https://buff.ly/34UrMWk