MLOps Explained | What is MLOps?

Get started with the basics and fundamentals of MLOps and learn how to put MLOps into practice. With MLOps, you will be able to streamline and manage your end-to-end machine learning lifecycle, from the inner loop of the data science lifecycle to the outer loop of model deployment and monitoring. In this session, Piethein will help you understand what is MLOps and how to put MLOps into practice with best practice recommendations, reference architectures, and hands-on examples.

Table of Contents:
00:00 – Introduction
06:02 – Recommended MLOps process
13:00 – Best practices for initiating a project
15:20 – Best practices for experimentation
18:56 – Best practices for data engineering
20:55 – Best practices for model operationalization
23:32 – Cluster vs. Spark Pools
28:05 – Organizational models for MLOps implementation
30:55 – Deployment
38:21 – Conclusion and QnA

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