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Showing posts with the label MLOps

MLOPS: Emerging best practices for deploying ML Models in production

It comes as no surprise that machine learning models are in production systems right now. How a machine learning algorithm got there is a little bit complicated story. So in the recently concluded MLOps (Machine Learning and IT Operations), that was held virtually from June 15th to 18th, one thing is clear, the proliferation of machine learning algorithms in production systems is a challenge to deploy. The theme of most of the talks in the conference is centered around taking software development practices and DevOps (software development and IT operations) and applying them to deploying machine learning algorithms. The workshop gave meaningful insights into how an organization can adapt some of the platforms presented at the conference. If we want to leverage machine learning algorithms in software products, we need a platform to consistently develop, test, and deploy machine learning algorithms in production. The workshop presented some of the platforms that can be used right now, li