Deploying ML Models in Production: An Overview

[@Erosis]

ML Ops is such a rarely taught topic in academia. Thank you so much for this explanation. I hope there is more to come!

[@ValerioVelardoTheSoundofAI]

Indeed. Most of the time, academia is focused only on the research side. Productisation is mainly done in the industry.

[@fcojperez]

Good summary of all different ML "framework" (if we may agree on that) to deploy a ML model. Thank for that 🙏

[@Diego0wnz]

Almost starting as a data science consultant and I really need this video series!!! Comes at perfect time

[@ValerioVelardoTheSoundofAI]

Nice! Good luck with the new enterprise :)

[@stefanvasilev8948]

Thank you very much! This was the most helpful resource I've found on the topic!

[@maxwohrle1049]

Great video as always. You really helped me a lot with my master thesis. This video series is yet another important building piece in dealing with audio machine learning projects. If I may add a comment. The Mnist dataset is a good example to demonstrate the deployment, but since the channel is called "the sound of ai" it would also be very interesting to see how to deploy a model that classifies an audio stream in real time.

[@ValerioVelardoTheSoundofAI]

Thank you Max. I will cover audio classification in realtime in a future series. I'd like to keep this mini-series is domain agnostic.

[@travelwithak_]

Thanks very much for the detailed explanation. Really helpful👏

[@AbdurrahimKururu]

this is very helpful thanks

[@ahmedgoniboulama8423]

Hello, great video, well explained, i would like to know if BentoML can be used to Deploy MeshSegNet models?

[@karndeepsingh]

Can you make a comparison video using ZenML and other MLOps tools?

[@sarthak7413]

Great Explanation..From where to get code files?

[@abdullrahmanelhayek2577]

Thank you so you amazing , videos , could you please make a vedio about how to use CHATGPT in programming

[@ValerioVelardoTheSoundofAI]

I recently created a voice assistant for ChatGPT. Check it out!

[@Coolblockj]

Hey! I've been trying to work on deploying some complex models and wondered if you had any experience in industry tools that do this well The scenario is essentially I have two models that need to be run, but one of the features they use is a completely separate model. Is there any industry standard software you know of to make that easier to do in a more scalable way? And if I eventually add more models that then depend potentially on those?

[@tirateable]

How are you? my question is different, please guide me I need to develop model language for Local language for speech recognation!

[@arumugam2615]

Great ...

[@sudharsankp]

I was really hoping if someone in the audio domain talks about deploying an speech model and give some pointers on ML Observability.

[@ValerioVelardoTheSoundofAI]

I won't be talking specifically about audio models in the next video. However, the same steps apply also in audio processing.

[@noahdrisort2005]

Currently I use torchserve

[@ValerioVelardoTheSoundofAI]

That's a good option!