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Google Cloud Professional Data Engineer Cert Prep: 3 Operationalizing Machine Learning Models
Via LinkedIn Learning
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Overview
“Google Cloud Professional Data Engineer Cert Prep: 3 Operationalizing Machine Learning Models” is part of the certification preparation series for aspiring Google Cloud Professional Data Engineers. This course focuses on the essential practices and tools required to operationalize machine learning (ML) models effectively in production environments using Google Cloud Platform (GCP). Participants will learn how to deploy, monitor, and maintain ML models at scale with services such as Vertex AI, AI Platform, Cloud Functions, and Big Query ML. The course...
Syllabus
Introduction
- Course overview
1. Pre-built ML Models as a Service
- Google Colab with TensorFlow Hub
- Using GCP NLP from the CLI
2. Training and Serving Infrastructure Selection
- PyTorch pretrained model overview
- Demo: PyTorch pretrained model
- Understanding TPUs
- TPUs as part of technology transition
- Getting started with Vertex AI
- Using GCP ML API vision from CLI
3. ML Model Measurement, Monitoring, and Troubleshooting
- Using the five whys method
- Demo: Load testing with Locust
- MLOps on GCP
Conclusion
- Using Google machine learning courses
- Next steps
Instructor
Noah Gift
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