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1
- Intro
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- Agenda
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- Challenges of ML Workloads
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- Introduction of MLOps
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- MLOps on Google Cloud
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- Managing models and tracking model quality
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- Demo: Create a Vertex Pipeline
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- Demo: Manage Models with Model Registry
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- Demo: Deploying to Endpoints and Model Monitoring
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- Customer success story
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- Summary
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- Want to find out more?
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- Coming next
Description:
Explore the world of MLOps in this 22-minute video from the Google Cloud Technical Guides for Startups - Grow Series. Dive into the challenges of ML workloads and discover how MLOps can accelerate model deployment on Google Cloud. Learn about managing models, tracking model quality, and creating Vertex Pipelines through hands-on demonstrations. Gain insights on using Model Registry, deploying to endpoints, and implementing model monitoring. Hear a customer success story and get a comprehensive summary of MLOps benefits. Access additional resources and links to deepen your understanding of MLOps on Google Cloud and stay tuned for upcoming episodes in the series.

Accelerating Model Deployment with MLOps - Google Cloud Technical Guide for Startups

Google Cloud Tech
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