We Raised $8M Series A to Continue Building Experiment Tracking and Model Registry That “Just Works”
Polyaxon vs Neptune
Which tool is better?
Neptune gives you a lot of flexibility and control on what you want to track and analyse and how you want to do it. It fits into any workflow and is adaptable. Manage users in a hosted or on-prem application, and get dedicated user support with Neptune!
Why Choose Neptune over polyaxon?
Neptune is lightweight (quick to learn and easy to master) and can serve all the experiment tracking needs of your team (any language, any framework, any infrastructure).
It lets you manage user access and gives you visibility into your team’s progress at any time with a great user-friendly UI.
Polyaxon tries to cover a larger part of the ML lifecycle and because of that is a less focused and heavier solution.
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- Free for individuals, non-profit and educational research
- Team: from $49
- Enterprise: from $499
- Free: 1 user
- Unlimited private and public projects
This page was updated on 28 April 2020. Some information may be outdated.
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The most lightweight experiment management
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Why Neptune is the Best Alternative to polyaxon
Is it instantaneous to start using polyaxon without contacting sales or setting up a server cluster?
With Neptune you simply register, install an open source neptune-client and you are ready to track experiments and collaborate in a team. You can manage user permissions and share experiments in the beautiful UI with no additional overhead. Powerful, simple, and available for you and your team in minutes.
Can you scroll through your images and charts?
Neptune lets you log images and charts to multiple image channels and scroll through them to quickly see the progress of your model training. Get a full picture of what is happening in your training and validation loops by leveraging more information!
Does polyaxon snapshot your Jupyter notebooks automatically?
Neptune notebook integration automatically snapshots your .iipynb whenever you run a cell with neptune.create_experiment() in it. Whether you remember to submit your experiment or not everything will be safely versioned and ready to be explored.
Does polyaxon let you fetch your experiment dashboard directly to a pandas DataFrame?
With Neptune you can fetch whatever information you or your teammates tracked and explore it however you like. We have some nice exploratory features, like HiPlot integration to help you with that.
neptune.init('USERNAME/example-project') make_parallel_coordinates_plot( metrics= ['eval_accuracy', 'eval_loss',...], params = ['activation', 'batch_size',...])
Does polyaxon let you track your exploratory analysis?
Neptune goes beyond the tracking of machine learning experiments and allows you to version your exploratory data analysis or results exploration as well!
Once it is saved in Neptune you can name, share, download or see diffs of your notebook checkpoints.
Do you have to create and maintain custom loggers for Skorch or PyTorch Ignite?
Neptune has integrations with every PyTorch Ecosystem library to let you start tracking your experiments in minutes!
# Skorch net = NeuralNetClassifier(...callbacks=[NeptuneLogger(...)]) net.fit(X, y) # Pytorch Ignite npt_logger = NeptuneLogger(...) npt_logger.attach(trainer) trainer.run(...) # Pytorch Lightning trainer = Trainer(logger=NeptuneLogger(...)) # Catalyst runner = SupervisedNeptuneRunner() runner.train() # Fastai learn.callbacks.append(NeptuneMonitor()) learn.fit_one_cycle(...)