Waabi
New Yorker
Bosch
NNaisense
Roche
Respo Vision
Samsung
Brainly
Workable
Solarwinds
Continuum Industry
Wefox
Customers
See how ML teams solve their experiment tracking problems with Neptune
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ML engineers and data scientists
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Commercial and research teams
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Projects tracked
Neil Isaac
Senior Staff Software Developer at Waabi
Organic adoption by our teams has been a key indicator that the tool has added value to their workflows and that they have been able to use it successfully.
Collaboration
Monitoring
Tracking
Hubert Bryłkowski
Senior Machine Learning Engineer at Brainly
Neptune’s UI and the front-end work great, and you don’t feel that you ‘fight’ with it. So instead of ‘fighting’ the tool, the tool itself is helping.
Collaboration
Monitoring
Reproducibility
Andreas Malekos
Head of Artificial Intelligence at Continuum Industries
Gone are the days of writing stuff down on google docs and trying to remember which run was executed with which parameters and for what reasons. Having everything in Neptune allows us to focus on the results and better algorithms.
Collaboration
Comparison
Debugging
Monitoring
Viet Yen Nguyen
CTO at Hypefactors
Neptune made sense to us due to its pay-per-use or usage-based pricing. Now when we are doing active experiments then we can scale up and when we’re busy integrating all our models for a few months that we scale down again.
Collaboration
Nicolas Lopez Carranza
DeepChain and BioAI Lead at InstaDeep
I like that Neptune does not get in your way – it is not very intrusive. It also does very well with the comparison of runs, sharing, and working collaboratively.
Collaboration
Wojtek Rosiński
Chief Technology Officer at ReSpo.Vision
If we can choose the best-performing model, then we can save time because we would need fewer integrations to ensure high data quality. Customers are much happier because they receive higher quality data, enabling them to perform more detailed match analytics.
Collaboration
Debugging
Monitoring
Reproducibility
Dr. Robert Toth
Founder of Theta Tech AI
Neptune and Optuna go hand in hand. You should start using Neptune as early as possible to save the trouble of having to go through multiple log statements to make sense of how your model did.
Collaboration
Debugging
Reporting
Patryk Miziuła
Senior Data Scientist at deepsense.ai
At a certain stage of machine learning maturity the need for a tool like this one rises naturally. And then Neptune is a solid choice because of low entry threshold, many useful features, and good documentation and support.
Collaboration
Comparison
Reporting
Versioning
