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Course Outline
Introduction
Overview of AutoML Features and Architecture
- Google’s Machine Learning ecosystem for government
- AutoML line of products for government
Working With Google’s Machine Learning Ecosystem for Government
- Applications for AutoML products in the public sector
- Challenges and limitations for government use
Evaluating Content Using AutoML Natural Language for Government
- Preparing datasets for government applications
- Creating and deploying models within government workflows
- Text and document training (classification, extraction, analysis) for government documents
Classifying Images Using AutoML Vision for Government
- Labeling images in government contexts
- Training and evaluating models for government use
- AutoML Vision Edge for on-premises government solutions
Creating Translation Models Using AutoML Translation for Government
- Preparing datasets (source and target languages) for government communications
- Creating and managing models within government systems
- Testing models to ensure accuracy for government use
Making Predictions from Trained Models for Government
- Analyzing documents for government reports
- Image prediction for government imagery
- Translating content for government publications
Exploring Other AutoML Products for Government
- AutoML Tables for structured data in government databases
- AutoML Video Intelligence for video analysis in government contexts
Troubleshooting
Summary and Conclusion
Requirements
- Basic understanding of data analytics for government
- Familiarity with machine learning techniques
Audience
- Data scientists for government
- Data analysts for government
- Developers for government
7 Hours
Testimonials (1)
Responses with solutions and practical use.
