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I would like to use it but I think the price doesn't justify the tool. For a team of 5 people github is $25 a month, you are $745 a month. I do understand a price a bit higher that github but not 30 times more expensive.
CometML vs Tensorboard? Thanks in advance for your feedback.
If you're already using Tensorboard just throw in our one liner: comet_ml.experiment(api_key="your-key") and you'll get everything TB gives you + our added value.
Great to see ML "governance" work being done on the training-part of the pipeline. Seems like this provides a Domino Data Labs based dashboards but without the walled garden environment. I've yet to see similar great initiatives also tackling the deployment-part. E.g. something similar you can stick on top of your model's API (or scheduled batch predictive outputs), as well as incoming instances, to monitor usage pat…
Hi, I’m one of the founders of Comet.ml. We built comet.ml to allow machine learning teams to automatically track their machine learning code, experiments, hyperparameters and results. We think that reproducibility is really important so we’re also giving free access to students, academics and open source projects. Feedback is welcome. Ask me anything.
Hi, looks great! Love the feature of tracking code changes. But how does this work? Does it upload the code to the servers every time I launch a training?
Earlier quoted context omitted.
Hi, looks great! Love the feature of tracking code changes. But how does this work? Does it upload the code to the servers every time I launch a training?
It depends if it's a git project but pretty much yes.
Earlier quoted context omitted.
It depends if it's a git project but pretty much yes.
So you would considered the latest committed version as the 'code of the current experiment'? Maybe to rephrase: I start a training with my local code and then I change one variable in the code or comment some processing and start the next training. Would I need to do something for comet to know how the code has changed?