AWS Summit ANZ 2022 - End-to-end MLOps for architects (ARCH3) 

Best AI architecture talk so far. She is very hard-core and geared towards practical engineers, not idiots expecting to watch 2 hours of fancy PPTs.

I have been working in MLOps for last 3 years and it's the best resource available on youtube for architecting MLOPs process.

Small MLOps architecture completed @ 11:50 Medium MLOps architecture completed @ 15:45 Large MLOps architecture completed @ 20:40

As a new MLOps engineer at NatWest, I found this video "AWS Summit ANZ 2022 - End-to-end MLOps for architects (ARCH3)" to be incredibly informative and helpful. The speakers provided a comprehensive overview of the key concepts and principles of MLOps, as well as real-world examples and case studies. I particularly appreciated their insights on how to implement MLOps in a large enterprise setting. Overall, I highly recommend this video to anyone who wants to learn more about MLOps or advance their career in this field.

One of the best talks on MLOps! Kudos to the presenter for condensing so much information in such a short amount of time. The diagrams and the presenter's narration are super clear.👏👏👏

I was searching for some real MLOps architecture examples with commentary and there is almost no content like this on YT. Thank you for this video. Great density of information also :)

New to an ML ops team and can't agree more with the comments. Even in 2024, this is still a great primer for a devops guy getting asked to convert to MLOps. Thanks!

This is PURE GOLD!

Your explanation of E2E ML architecture is fantastic! You managed to condense what would have taken me hours of reading and research into a clear and concise 23-minute presentation with great examples. Thank you for making such a complex topic so easy to understand. Perhaps sharing the Cloudformation scripts would save all massive amount of time to start exploring the services.

This is by far the best MlOps yt vid out there

Thanks for the video. You accurately talked about various points in the ML pipeline.

Thank you for putting out this video, really helpful!!! Helped me clearly understand how MLOps can be leveraged at different hierarchies.

Very interesting talk, is it possible to access the architecture diagrams?

I love the takeaway she gave in the end of talk

👍really intrigued my interest on MLOPS. Chose this over IPL live, that's how interesting this is for me :) Concise and to the point. Not a single minute wasted. :) :)

The amount and way of information that is presented in the video is amazing. Thanks!!

Really good presentation and ideas for MLOps architectures. Thanks for sharing!

This is a great presentation and sounds lovely when looking at diagrams but most of the issues with AWS is that things rarely work as smooth in practice once you actually start using the services.

Thanks for the great presentation.

thanks for this !! Can we implement most of this if we are deploying to an edge device?? Any major major changes.

Great Talk on AI/ML architecture. kudos to the presenter. can anyone help me find those whitepaper links that were mentioned at the end of presentation?

Very well explained

I loved this video

Great explanation. Thanks for sharing

great!! thankyou!!

amazing!

For Medium MLOps architecture what is the point in monitoring the model in the Staging environment? Monitoring production models are enough I guess. Please help me understand

Amazing video, But what about metadata store, and experimentation tracking I can't seem to find it on the architecture

How does the approval process work? Do we need to approve each version that comes in or perhpas approve one model over some period e.g. a day?

Superb!! Just what I needed🙂

awesome.

Awesome

oooo she looks like a fun person

Can I get these slides?

Great talk the best on MLOps on RU-vid, can anyone give me resources to include offline or online feature pipelines with feature stores?

Awesome, indeed!

How can I download the slides of this talk?

ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-UnAN35gu3Rw.html Why is it necessary to re-deploy the Production services every time a new model version is deployed?

Hall Charles Gonzalez Daniel Walker Richard

This is amazing

Where can I get slides?