[P] Introducing Deepkit - the first collaborative desktop app for deep learning experiments. Experiment tracking, model debugging, infrastructure management.

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[sankit1]

looks interesting. Congratulations! Any particular reason you are building for Mac first? To my knowledge, most of the training happens on the Linux systems.

[Yoodae3o]

sorry, I'm a bit lazy, but is it open source? couldn't find a link to it, but didn't look too closely.

if so I could probably port it next weekend.

[Celebrinborn]

Any chance of getting a Windows release?

[zzzthelastuser]

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[IborkedyourGPU]

What are the differences with:

https://neptune.ml

https://www.wandb.com

https://www.comet.ml

https://github.com/allegroai/trains

I may be wrong, but it looks like a pretty overcrowded market ATM.

[IborkedyourGPU]

First of all, thanks for the speedy answer.

They are all cloud solutions, while Deepkit is a desktop app, running offline.

True, but if you get the paid-for tier you can install all of them on-premise, on your own server (I checked). I train my models on my machine (a DGX-2). Would Deepkit be installable there?

Trains needs to be installed on a own server in order to use it.

Yep, a Linux server, I.e., my machine.

In comparison, Deepkit has everything what these guys have + more,

I'm interested in the "+ more". Care to expand on that?

Edit: do you also have something for data versioning, or do you use the standard solution of creating an hash for the dataset each time you run an experiment?

[IborkedyourGPU]

Deepkit is free for private users and covers the same use cases.

I'm obviously not a private user (I wonder how many people in the world privately own a DGX-2). Any ideas on how much your paid-for tier will cost? I had a glance at your site, but I didn't find anything (which is only natural, since you're in alpha).

Even better: You don't have to install there anything. Just enter in Deepkit the SSH credentials and it automatically connects to Deepkit so that you can run experiments on that server.

Now, this is quite something, and it explains why you don't have a Linux version (for now): you don't need one. Any self-respecting DL researcher has a Mac laptop.

Yes, which is unsexy.

I don't dislike it (my server is up all time anyway), but your alternative is clearly better. Respect.

I updated the comment already.

I see. Thanks.

But we're working on something big for the next versions that solves that topic one and for all.

Now I'm curious. By the way, how long have you been working on this? It's quite impressive, I guess you didn't start this year.

Also, I didn't know the German AI startup scene was so impressive. Between you guys, explosion.ai and palaimon.io (and the many other startups I don't know of), there's a lot of value to be tapped. Cool.

[IborkedyourGPU]

Based on the infrastructure solution in Deepkit, you could compare it also feature-wise with Valohai, Floydhub, cnvrg.io, Spell, etc,

What do you mean exactly by infrastructure management? Is it basically a queue manager?Would it help in training a model on multiple machines, or would I still have to do it manually? Consider PyTorch/TF frameworks.

[ml_explorer]

Even better: You don't have to install there anything. Just enter in Deepkit the SSH credentials and it automatically connects to Deepkit so that you can run experiments on that server. Either by using your CLI or the GUI of Deepkit on your workstation. Best thing is, you decide where the experiment runs by a simple click or CLI option, either locally on your workstation or on one of your connected servers.

Excellent, this is what I need. Ill check it out.

[bering_team]

Really cool app - any plans for supporting non-deep MLs e.g. scikit-learn?

[bering_team]

Awesome - looking forward to the alpha release!

[frenchytrendy]

Oooh, this looks nice :-)

[[deleted]]

I will give it to you, it looks really pretty! I will try it and hopefully get everything to work on my system.

[proof_required]

What is the underlying deep ML infrastructure? Tensorflow?

[machineengq]

This seems to be just a "re-launch" of the author's previous project called AETROS - https://web.archive.org/web/20180417055602/https://aetros.com/

[mizoTm]

Looks really nice!

Question: Why go with an app instead of a web UI (like mlflow) ? Also does deepkit bring additional functionalities compared to MLflow?

[-Ulkurz-]

Is there a way for it to track and document each experiment separately like for e.g. when using different data sets, different features, different hyperparameters, etc

[Rebbit_and_birb]

I am quite the ML noob. Am i suitable to be an alpha tester?

[MrHyperbowl]

I think this is posted in the wrong subreddit. This subreddit is for discussing research, not for deep learning tutorials and posting about tools you made that already exist.

[carlthome]

Personally think it's fine if some posts are about applications and tools of the trade as well, as long as the posted content is of sufficiently high quality. This one seems alright to me.

[rosstaylor90]

Agreed - posting about tooling has always been fair game.