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Deploying Machine Learning Models to Production: Challenges & Solutions

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Duration

31m

level

Intermediate

Course Creator

DevSecCon

Last Updated

25-Jan-24

In this presentation, you will look at the top challenges you face deploying machine learning models to production and how to tackle those challenges using MLOps.

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For the most part, machine learning is similar to traditional software development and most of the principles and practices that apply to traditional software development also apply to machine learning. However, are certain unique challenges that come with deploying ML models to production. In this presentation, you will look at the top challenges you face deploying machine learning models to production and how to tackle those challenges using MLOps. Key takeaways include: How machine learning differs from traditional software development, the top challenges when deploying ML models to production, what MLOps is and how to tackle ML specific challenges, and anecdotes from deploying ML models using industry principles and best practices.
Author Name: DevSecCon
Author Description:
DevSecCon is the global community dedicated to DevSecOps to help implement security in the overall development process. If you’re a security enthusiast & you want to learn more about how to better secure your team, then check out our community & resources.

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Deploying Machine Learning Models to Production: Challenges & Solutions
Deploying Machine Learning Models to Production: Challenges & Solutions
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