Eric Anderson (@ericmander) and Simba Khadder (@simba_khadder) explore Featureform, the “virtual” feature store platform that aims to standardize data pipelines for machine learning. Contributor is no stranger to feature stores, but Simba has a broader definition than most. Join us to learn how Featureform enables data scientists and machine learning practitioners to solve a common, but rarely addressed organizational problem.

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In this episode we discuss:

• How there is no standard or north star for MLOps
• Why enterprise is where Featureform’s value shines
• MLPlatform problems vs MLOps problems
• Why copy/paste and Git don’t cut it
• Deploying MLOps solutions that make data scientists and everyone else happy

Links:

• Featureform
• Terraform
• Apache Spark
• Feathr

Other episodes:

• Tensorflow with Rajat Monga