MLOps (a compound of “machine learning” and “operations”) is a practice for collaboration and communication between data scientists and operations professionals to help manage the production machine learning lifecycle. Similar to the DevOps term in the software development world, MLOps looks to increase automation and improve the quality of production ML while also focusing on business and regulatory requirements. MLOps applies to the entire ML lifecycle - from integrating with model generation (software development lifecycle, continuous integration/continuous delivery), orchestration, and deployment, to health, diagnostics, governance, and business metrics.
In this webinar, we’ll discuss core practices in MLOps that will help data science teams scale to the enterprise level. You’ll learn the primary functions of MLOps, and what tasks are suggested to accelerate your team's machine learning pipeline. Join us in a discussion with data science experts from cnvrg.io, and learn how teams use MLOps for more productive machine learning workflows.
Key webinar takeaways:
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Paint a mental image of the benefits of attending your webinar. Often times this can be summarized in the title of your event. Your prospects may not even make it to the body of the message, so get your point across immediately. Capture their attention, pique their interest, and push them towards the desired action (i.e. signing up for your event). You have to make them focus and you have to do it fast. Using an active voice and bullet points is great way to do this.
Always add key takeaways. Something like this....In this session, you’ll learn about: