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Duration 14 hours
Course Outline
Foundations of Azure Machine Learning
- Overview of AML features and system architecture
- Understanding end-to-end workflows within AML (Azure ML pipelines)
- Guided navigation of Azure Machine Learning Studio
Data Handling and Model Construction
- Techniques for data preparation
- Constructing machine learning models
- Processes for training and testing models
Evaluating Model Performance and Stability
- Utilising validation metrics for ML models
- Strategies for managing and preventing overfitting
Managing and Deploying Models
- Registering trained models
- Building model images
- Executing model deployment
Basics of the OpenAI API on Azure
- Introduction to the OpenAI API
- Setting up API configurations and authentication
Retrieval and Application Integration
- Managing documents with AI Search
- Incorporating OpenAI models into application logic
Customisation and Production Best Practices
- Fine-tuning and customising models
- Adhering to best practices in production environments
Wrap-up and Pathways Forward
Requirements
- Familiarity with Python and fundamental machine learning principles
- Practical experience with REST APIs or SDKs
- General knowledge of Azure service ecosystem
Who Should Attend
- Data scientists and ML engineers
- Application developers implementing AI functionalities
- Technical leads and solution architects
Testimonials (1)
the instructor :)
