62 Neptune.ai Testimonials

“Within the first few tens of runs, I realized how complete the tracking was – not just one or two numbers, but also the exact state of the code, the best-quality model snapshot stored to the cloud, the ability to quickly add notes on a particular experiment. My old methods were such a mess by comparison.”

“The problem with training models on remote clusters is that every time you want to see what is going on, you need to get your FTP client up, download the logs to a machine with a graphical interface, and plot it. I tried using TensorBoard but it was painful to set up in my situation. With Neptune, seeing training progress was as simple as hitting refresh. The feedback loop between changing the code and seeing whether anything changed is just so much shorter. Much more fun and I get to focus on what I want to do. I really wish that it existed 10 years ago when I was doing my PhD.”

“What we like about Neptune is that it easily hooks into multiple frameworks. Keeping track of machine learning experiments systematically over time and visualizing the output adds a lot of value for us.”

“Neptune was easy to set up and integrate into my experimental flow. The tracking and logging options are exactly what I needed and the documentation was up to date and well written.”

"Building something like a power line is a huge project, so you have to get the design right before you start. The more reasonable designs you see, the better decision you can make. Optioneer can get you design assets in minutes at a fraction of the cost of traditional design methods."

"When I joined this company, we were doing quite many different experiments and it’s really hard to keep track of them all so I needed something to just view the result or sometimes or also it’s intermediate results of some experiments like what [does] the data frame look like? What [does] the CSV look like? Is it reasonable? Is there something that went wrong between the process that resulted in an undesirable result? So we were doing it manually first but just writing some log value to some log server like a Splunk."

"Speed, accuracy and reliability are of the essence. That’s what we like about Neptune. Its lightweight SDK seamlessly integrates with our machine learning workflows, enabling us to effortlessly track artifacts and monitor model performance metrics and empowering our team to iterate rapidly, ensuring repeatable and reliable results."

“Neptune provides an accessible and intuitive way to visualize, analyze and share metrics of our projects. We can not only discuss it with other team members, but also with management, in a way that can be easily interpreted by someone not familiar with the implementation details. Tracking and comparing different approaches has notably boosted our productivity, allowing us to focus more on the experiments, develop new, good practices within our team and make better data-driven decisions. We love the fact that the integration is effortless. No matter what framework we use – it just works in the matter of minutes, allowing us to automate and unify our processes.”

“I tested multiple loggers with pytorch-lightning integrations and found neptune to be the best fit for my needs. Friendly UI, ease of use and great documentatinon.“

“The last few hours have been my first w/ Neptune and I’m really appreciative of how much time it’s saved me not having to fiddle w/ matplotlib in addition to everything else.“

“I am super messy with my experiments, but now I have everything organized for me automatically. I love it."

“Indeed it was a game-changer for me, as you know AI training workloads are lengthy in nature, sometimes also prone to hanging in colab environment, and just to be able to launch a set of tests trying different hyperparameters with the assurance that the experiment will be correctly recorded in terms of results and hyper-parameters was big for me.”

"We tried MLflow. But the problem is that they have no user management features, which messes up a lot of things."

"My productivity in collaborating with students and also my own research speed increased dramatically. I wouldn’t know how to do my work without Neptune."

"When working with projects that had thousands of runs, loading the interface and sorting through data was super slow in Weights & Biases. Neptune is better at handling large-scale. We’re happy with this choice."