Deploy ML model in 10 minutes. Explained

Level up your Data Science to Machine Learning Engineering.
Docker engine download: docs.docker.co...
Repo with code from video: github.com/Dan...
Study
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MACHINE LEARNING DEPLOYMENT INTO PRODUCTION ENVIRONMENT
Course 1 (Intro in ML in prod): imp.i384100.ne...
Course 2 (ML&Data Lifecycle in prod): imp.i384100.ne...
Course 3 (ML Modeling and Deployment in prod): imp.i384100.net/eKVXgO
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DOCKER & KUBERNETES (best course out there)
tinyurl.com/25...
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[@jawaharkonathala6950]

Nicely explained. I just wanted this much info only, saved myself from taking a 3-hr coursera course. Thank you

[@lifecrunch]

Glad it was helpful!

[@orilio3311]

Yeah same here :))

[@piano_tam97106]

Very nice video and clearly explain
Currently i am learning about ci/cd and cloud deploy for ml project, could you kindly please do a video on that subject?

[@lifecrunch]

Coming up shortly.

[@sangeethag8228]

Thanks a lot Danil.. You saved 4hrs of time. Its working for me :)

[@lifecrunch]

Glad it helped!

[@eswarkarthikk9571]

i bild a object detection model . that was 180mb in size . how can i deploy my model

[@lifecrunch]

That’s an open ended question. Deploy where? I have a few videos on the subject, check them out.

[@vasimSyed-e9d]

@Danil_Zherebtsov
please create video on roadmap of mlops, and also end-to-end mlops projects, with and without open-source tools projects

[@lifecrunch]

Thanks for the comment. I’ll consider this

[@vasimSyed-e9d]

@@lifecrunch please upload fast as soon as possible, eagerly waiting here

[@alikograce.5520]

Nicely explained, please will it be the same steps for a pikl file ?

[@lifecrunch]

Yes, pickle is just a different container. The only thing to change in this case is the model loading part with pickle instead of joblib. The rest will be the same.

[@doneaabohlassan1995]

The commands in terminal work in os Windows?

[@lifecrunch]

I haven’t touched a windows machine is a decade, so can’t be certain, but I’m pretty sure that some modifications will be necessary.
You may have to change the slashes direction in all the paths.

[@ghostpasha1954]

thanks bro you explain so good God with you !

[@lifecrunch]

Happy to help

[@ihorrible]

Seems Hard)

[@lifecrunch]

The intention was to show how easy it actually is 😉

[@EmmanuelSalvo-eh6ow]

How or where can we deploy that Docker container to be used along the internet?

[@piano_tam97106]

AWS or GCP, Azure i guess, every company now require every machine learning engineer to know about CI/CD pipeline, have experience with cloud service, or at least that is my point of view from recently job interview that i got deny :>> Gotta learn a lot lot more

[@EmmanuelSalvo-eh6ow]

@@piano_tam97106 I'm sorry to hear that, thanks for the reply, good luck!

[@lifecrunch]

I guess I need to make a separate video on this subject. Stay tuned.

[@Sherry-g12]

Thanks a lot for the great video. Somehow the links for course 3 and 4 are invalid. Could you please help update the links?

[@lifecrunch]

Updated. The problem was that courses 3 and 4 were merged together and had a new link. I've posted the updated link.

[@shr00shr]

Thanks, Danil ! This is exactly what I was looking for. Clear and concise tutorial,🙏

[@lifecrunch]

Glad it was helpful!

[@TSSsniper]

Very informative.

[@lifecrunch]

Thanks!

[@julien957]

Do you know if the problem of compatibility between M chips and Docker is solved?

[@lifecrunch]

I know that the problem exists, but I’ve never encountered it. In my case Docker had been working perfectly fine.
I guess compatibility issues arise only with certain OS versions.

[@liambchops]

This is awesome. Thank you for posting

[@lifecrunch]

Thank you for watching!

[@avinasha3603]

Thank you !

[@lifecrunch]

You're welcome!

[@HZN2502]

👑🙌🙌

[@thevicky1428]

Can I do llama 8b fine tuned with this sir ?

[@lifecrunch]

With what? Docker??

[@thevicky1428]

@@lifecrunch yeah, I fine tuned unsloth llama 8.1 how to deploy that with docker or cloud providers

[@lifecrunch]

@@thevicky1428 Just like any other model. Write the inference script to query the model with prompts or whatever you want to query it with, configure docker as explained in the video, save all the required llama artifacts into the corresponding directories and there you go. Basically repeat all the steps from the video only replacing the 'predict()' function with your llama inference code.

[@thevicky1428]

@@lifecrunch thanks sir

[@Adebowale279]

This is just wonderful and succinct. Thank you!

[@lifecrunch]

Thank you for watching!

[@grsdjjggfss3373]

❤❤❤❤❤❤❤

[@siddharthapachourey1706]

remove background audio track its distracting

[@lifecrunch]

Thanks for the feedback. Unfortunately, published videos cannot be amended.

[@dataworldsolution]

Thanks Sir

[@lifecrunch]

Welcome!

[@bhaviksonule-bq9dn]

Can we do the same with open source model?

[@lifecrunch]

What do you mean by open-source model?
If you have any trained model and code to inference it - you can deploy it.

[@bhaviksonule-bq9dn]

Thank you for your reply, i think I got it.

[@СтаниславКолчин-н7ы]

soo good

[@lifecrunch]

Thanks man!

[@Swilem999]

The most underrated channel i have ever seen , you give a very nice content and information with a very simple way , thank you very much

[@lifecrunch]

Thank you!

[@kali6509]

/bin/sh: 1 : [uvicorn,: not found

[@lifecrunch]

A little more context wouldn’t hurt

[@august8877]

"PromoSM" 🤤

[@lifecrunch]

There is nothing to promote here. Common practice.