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Duration 14 hours
Course Outline
Foundations of Azure Machine Learning
- Overview of AML capabilities and architectural design
- Understanding the full AML workflow (Azure ML pipelines)
- Guided navigation of Azure Machine Learning Studio
Data Handling and Model Construction
- Data preprocessing and preparation
- Architecting the model structure
- Executing training and testing phases
Assessing Model Performance and Reliability
- Selecting appropriate validation metrics for ML models
- Mitigating and avoiding overfitting issues
Managing and Deploying Models
- Registering trained models for reuse
- Generating model images
- Deploying models to production environments
Basics of the OpenAI API on Azure
- Introduction to OpenAI API functionalities
- Configuring and authenticating API access
Retrieval and Application Integration
- Managing documents via AI Search
- Embedding OpenAI models into application logic
Customization and Production-Ready Strategies
- Refining models through fine-tuning or customization
- Applying best practices for production stability
Wrap-up and Future Directions
Requirements
- Familiarity with Python and core machine learning principles
- Hands-on experience with REST APIs or SDKs
- General knowledge of the Azure service ecosystem
Target Audience
- Data scientists and ML engineers
- Developers implementing AI functionalities
- Technical leads and solution architects
Testimonials (1)
the instructor :)
