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LinkedIn Learning

Leveraging Cloud-Based Machine Learning on Google Cloud Platform: Real World Applications

via LinkedIn Learning

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Overview

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Learn the basics of leveraging Google Cloud Platform for building AI-based applications. Explore the tools that you can use today, as well as best practices for using them correctly.

Syllabus

Introduction
  • Intro to artificial intelligence (AI) on Google
  • What you should know
1. AI Basics
  • AI processing and Google
  • Create a knowledge base
  • AI applications and Google
  • AI and cloud computing
  • AI and Google
2. Sample AI Use Case
  • Case study: International Drone Inc.
  • Identifying the need for AI
  • AI solution: Better inventory control
  • AI solution: Better manufacturing systems
  • ROI of AI inclusion
3. GCP Vision AI
  • Vision AI build
  • Vision AI training
  • Vision AI deployment
  • Demo: Vision AI
4. GCP Kubeflow
  • Kubeflow overview
  • Set up Kubeflow
  • Kubeflow integration
  • Execution
5. GCP AI Application Walk-Through
  • Identify requirements
  • Design an AI system for GCP
  • Build
  • Train
  • Deployment
6. Other Considerations
  • AI's impact on performance
  • Estimate cost of AI integration
  • Operations best practices
  • Security considerations
  • Governance
Conclusion
  • Additional resources

Taught by

David Linthicum

Reviews

4.6 rating at LinkedIn Learning based on 29 ratings

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