Deploying machine learning models to serverless architecture is necessary for enterprises looking to scale their operations while maximizing resource utilization and minimizing infrastructure costs. Capital One’s ML engineering manager Fatma and data science manager Lina will discuss the benefits of migrating ML models to serverless, and how to navigate potential challenges and considerations before migrating.
For more insights on serverless at scale, check out our resources at https://i.capitalone.com/JeJ0os5hE

Chapters
0:00 Moving our ML model to serverless architecture
1:26 Benefits of serverless ML
1:46 Serverless architecture isn’t for every ML model
2:18 Challenge #1: Running time
3:03 Challenge #2: Memory
5:03 Tip #1: Start from the cloud
5:24 Tip #2: Choose the right serverless option for your use case

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