MLOps Community
+00:00 GMT
Sign in or Join the community to continue

Argo Workflows

Posted Jul 28, 2022 | Views 842
# Argo Workflows
# MLOps Stack
# Artifact Storage
# Beat
Share
speakers
avatar
Kemal Tugrul Yesilbek
Senior Machine Learning Engineer @ Beat

Kemal is a Senior Machine Learning Engineer at Beat, one of the fastest-growing ride-hailing apps in Latin America. He studied software engineering and machine learning. During his time in academia, he published machine learning solutions approaching human-level performance.

Kemal started his career as a data scientist. He founded Elify.io, a skill assessment tool for data-driven roles, which resulted in an exit. He is working as a machine learning engineer for the past years, delivering end-to-end machine learning backed solutions.

+ Read More
avatar
Ben Epstein
Founding Software Engineer @ Galileo

Ben was the machine learning lead for Splice Machine, leading the development of their MLOps platform and Feature Store. He is now a founding software engineer at Galileo (rungalileo.io) focused on building data discovery and data quality tooling for machine learning teams. Ben also works as an adjunct professor at Washington University in St. Louis teaching concepts in cloud computing and big data analytics.

+ Read More
SUMMARY

One of the most popular, and useful, ways to productionize a machine learning solution is scheduled batch workflows. In this approach, we deliver predictions in regular intervals. There are many tools available allowing you to construct and schedule your workflows. When there are many options, it can be difficult to choose.

In this session, we talk about Argo Workflows for batch workflows; how to build them; and why you may want to adopt them in your MLOps stack.

+ Read More

Watch More

Orchestrating Machine Learning Workflows with Prefect
Posted Mar 04, 2022 | Views 594
# Coding Workshop
# Presentation
# ML Orchestration
# Prefect
# Prefect.io
Best Practices Towards Productionizing GenAI Workflows
Posted Apr 09, 2024 | Views 302
# GenAI
# Metaflow
# Outerbounds
# Outerbounds.com
MLOps EngineeringLabs: What We Learned Building End-to-end ML Applications on Flyte / How Flyte Orchestrates Tasks and Workflows
Posted Apr 27, 2022 | Views 792
# Product Development
# MLOps EngineeringLabs
# Flyte
# Union
# union.ai
# artefact.com
# Reply.com
# hurb.com