Build and deploy quality ML models with AI observability

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A major European bank was experimenting with machine learning models and wanted to deploy more of them at scale to bolster their overall security strategy. However, to ensure it retained the trust of internal and external stakeholders, the bank needed to be very responsible when testing, debugging, and monitoring its new applications.

In this case study, you’ll discover how the bank was able to reliably speed up ML model testing, approval, and deployment by leveraging a comprehensive AI observability solution. Read on to learn how you can ensure model quality for your AI solutions by focusing on testing and monitoring throughout the software lifecycle.

Vendor:
AWS & Intel
Posted:
Mar 13, 2024
Published:
Mar 13, 2024
Format:
PDF
Type:
Case Study
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