Build CI/CD Pipelines for ML Projects with Azure Devops |

Demonstrate and discuss how to automate an end-to-end ML/AI project. Will touch on DevOps tasks for data sanity test, model training on different compute targets, model version management, model evaluation/model selection, model deployment as real-time web service, staged deployment to QA/prod, integration testing and functional testing.
What will you learn from session - Devops best practices for ML projects.
Speaker Bio: Soniya Mehta
Soniya is an AI/ML professional working at EXL Healthcare, Chennai with an academic background in Statistics. Apart from ML development, her diverse work experience includes designing and building ML systems and platforms, model deployments and task automation. She's passionate about making AI accessible to all. She loves sharing and speaking at community events, is a cloud enthusiast and open-source aficionado.
Social Handle
LinkedIn- / soniyamehta
Pre-requisites:
Basics of Azure Devops is necessary.
[eventID:19134]

[@yashvats7815]

Could you guys provide any kind link where we can go through code

[@ikennacontrol]

great demo, and thanks for sharing. is there an accessible repository for this demo?

[@biswajit4631]

Please show us the content in your release pipeline, in azure cli

[@SantoshClouds]

Good Demo. can you please share the repo link and list of tasks in build pipeline

[@fabian6463]

thank you, where do I find the code?

[@rishikeshkumar2841]

Please show us the content in your release pipeline, in azure cli