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#211 Accelerating MLOps with Amazon SageMaker with Romina Sharifpour, Machine Learning Specialist at Amazon Web Services (AWS)

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Manage episode 344693141 series 2310475
Content provided by Felipe Flores. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Felipe Flores or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

In today’s episode, we have Romina Sharifpour, Machine Learning Specialist at Amazon Web Services (AWS).

Operationalising machine learning models, particularly scaling MLOps capability across teams within an organisation is a difficult feat.

Join Romina to find out how you can easily accelerate your MLOps journey using Amazon SageMaker Pipelines. You'll gain insights into how AWS customer Carsales keeps up with increased demand in building and productionising AI models, and their strategy to democratise AI across the whole development teams. This allows any developer to be a citizen data scientist and ML engineer by leveraging Amazon SageMaker.

Enjoy the show!

If you want to learn more about building modern applications on AWS and attend a virtual conference, just google “AWS Innovate” or click the link below.

https://aws.amazon.com/events/aws-innovate/apj/modern-apps/

Thank you to our sponsor, Talent Insights Group!

Join us in Melbourne for Scaling AI with MLOPS: https://www.datafuturology.com/mlops

Join our Slack Community: https://join.slack.com/t/datafuturologycircle/shared_invite/zt-z19cq4eq-ET6O49o2uySgvQWjM6a5ng

Read the full podcast episode summary here.

  continue reading

268 episodes

Artwork
iconShare
 
Manage episode 344693141 series 2310475
Content provided by Felipe Flores. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Felipe Flores or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

In today’s episode, we have Romina Sharifpour, Machine Learning Specialist at Amazon Web Services (AWS).

Operationalising machine learning models, particularly scaling MLOps capability across teams within an organisation is a difficult feat.

Join Romina to find out how you can easily accelerate your MLOps journey using Amazon SageMaker Pipelines. You'll gain insights into how AWS customer Carsales keeps up with increased demand in building and productionising AI models, and their strategy to democratise AI across the whole development teams. This allows any developer to be a citizen data scientist and ML engineer by leveraging Amazon SageMaker.

Enjoy the show!

If you want to learn more about building modern applications on AWS and attend a virtual conference, just google “AWS Innovate” or click the link below.

https://aws.amazon.com/events/aws-innovate/apj/modern-apps/

Thank you to our sponsor, Talent Insights Group!

Join us in Melbourne for Scaling AI with MLOPS: https://www.datafuturology.com/mlops

Join our Slack Community: https://join.slack.com/t/datafuturologycircle/shared_invite/zt-z19cq4eq-ET6O49o2uySgvQWjM6a5ng

Read the full podcast episode summary here.

  continue reading

268 episodes

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