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Understanding functional and technical aspects of Professional Machine Learning Engineer - Google ML Solution Architecture

The following will be discussed in Google Professional-Machine-Learning-Engineer exam dumps:

• Logging/management
• Choose appropriate Google Cloud hardware components
• Optimizing data use and storage
• Monitoring
• Feature engineering
• A variety of component types - data collection; data management
• SDLC best practices
• Serving
• Building secure ML systems
• Design architecture that complies with regulatory and security concerns
• Privacy implications of data usage
• Choose appropriate Google Cloud software components
• Exploration/analysis
• Data connections
• Automation of data preparation and model training/deployment
• Identifying potential regulatory issues
• Automation
• Design reliable, scalable, highly available ML solution
• Selection of quotas and compute/accelerators with components

Reference: https://cloud.google.com/certification/guides/machine-learning-engineer

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