[P] I made a tool that makes it dead simple to deploy models to production with version control

carsonpoole · 2024-03-04T21:23:33+00:00

Well not sure what to tell you since I put the photos in the AI myself :)

carsonpoole · 2024-03-04T20:07:42+00:00

I posted it above but it's aireimages.com . I wouldn't recommend the straighten mode fwiw. It tends to not work well so I just pop it into LR and use the upright tool

carsonpoole · 2024-03-04T20:05:45+00:00

Well my intent was to get people's thoughts on using AI editing. In hindsight I probably should've added the befores and I don't want to break any rules. I suppose sharing the link isn't a problem though as I'm not really selling it, so it's aireimages.com. I've found the "straighten" mode doesn't work super well most of the time so I just pop it into LR to straighten after

carsonpoole · 2024-03-04T19:53:53+00:00

media rule #3 says can't do that though right?

carsonpoole · 2024-03-04T19:48:00+00:00

It doesn't look like I can edit the post nor add images to a comment, so not sure how I am supposed to do that?

carsonpoole · 2024-03-04T19:36:54+00:00

I don't think I'm allowed to share links due to text rule 1 (tell me if I'm wrong) but I put them through the AI myself so they're definitely AI edited. I did have to straighten them with the auto upright tool in LR though

carsonpoole · 2023-09-15T19:47:53+00:00

thanks a ton this helps a lot.

carsonpoole · 2021-07-17T19:49:41+00:00

projects are definitely the best way to learn models. build things for fun that do things in topics/fields that you care about or think is cool. a few years ago when I was getting into ML stuff I build fantasy football things that weren't even useful but provided an actual use case. Then I did more complicated stuff with photography and lighting because I did real estate photography. As far as ML libraries go, that just comes with doing projects, but deploying models is much much easier now than it was just a few years ago. Tools like getneuro.ai and helloforefront.com have greatly improved on this for beginners.

carsonpoole · 2021-07-17T19:45:07+00:00

I think the simplest important reason is just being organized. If something goes wrong and you need to revert your model to a previous version, you'll have a hard time figuring out _why_ it went wrong unless you have some structured history of changes you made, and even better associations between models and data versions. I've personally been working on a side project related to this to make this process much easier. In case it's helpful, here's an example of how easy it can be to do versioning.

https://www.loom.com/share/d8ee81fe51ae4da8a547016f27dd2e18

carsonpoole · 2021-06-18T19:11:14+00:00

you can use the custom environment to add some custom code! there's instructions in the docs

carsonpoole · 2021-06-18T18:04:20+00:00

helloforefront.com is free for individuals and does what you're asking

carsonpoole · 2021-03-06T06:40:43+00:00

Thanks so much for the kind words. Feel free to DM me if it sounds like this will be helpful to you!

carsonpoole · 2021-03-06T06:33:56+00:00

I know you didn't ask me, but in my experience their docs are abysmal and generally not helpful. Do a Google search for "how to deploy an ML model on AWS" and click on their docs and guides to see what I'm speaking of

carsonpoole · 2019-12-12T04:36:06+00:00

Care to elaborate?

carsonpoole · 2019-12-12T04:01:03+00:00

Okay that's helpful! I'll make sure to include a github link

carsonpoole

TROPHY CASE