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Duration 14 hours
Course Outline
Foundations of Azure Machine Learning
- Exploring AML features and underlying architecture
- Understanding end-to-end workflows within AML (Azure ML pipelines)
- Navigating the Azure Machine Learning Studio interface
Data Processing and Model Construction
- Techniques for data preparation
- Constructing effective machine learning models
- Processes for training and testing models
Assessing Model Performance and Reliability
- Applying validation metrics to ML models
- Strategies for handling and preventing overfitting
Model Lifecycle Management and Deployment
- Registering trained models for version control
- Generating model images for containerization
- Executing model deployment tasks
Basics of the OpenAI API on Azure
- Introduction to the capabilities of the OpenAI API
- Configuring API settings and managing authentication
Data Retrieval and Application Integration
- Managing documents using AI Search
- Integrating OpenAI models into broader application architectures
Customization and Operational Excellence
- Refining models through fine-tuning and customization
- Adopting best practices for production environments
Wrap-Up and Future Pathways
Requirements
- A solid grasp of Python and foundational machine learning principles
- Practical experience working with REST APIs or SDKs
- Basic knowledge of the Azure service ecosystem
Target Audience
- Data scientists and ML engineers
- Application developers focused on building AI-driven features
- Technical leads and solution architects
Testimonials (1)
the instructor :)
