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Duration 14 hours
Course Outline
Foundations of Azure Machine Learning
- Introduction to AML capabilities and system architecture
- Understanding end-to-end workflows using AML (Azure ML pipelines)
- Guidance on navigating Azure Machine Learning Studio
Data Handling and Model Development
- Preparatory steps for data
- Constructing a machine learning model
- Processes for training and testing the model
Evaluating Models and Ensuring Reliability
- Key validation metrics for assessing ML models
- Strategies for managing and avoiding overfitting
Model Lifecycle and Deployment
- Registering trained models
- Generating model images
- Deploying models to production
Basics of the OpenAI API on Azure
- Overview of the OpenAI API
- Configuration and authentication methods for the API
Retrieval Strategies and Application Integration
- Leveraging documents with AI Search
- Integrating OpenAI models into application frameworks
Customization and Operational Best Practices
- Techniques for model fine-tuning and customization
- Best practices for maintaining production systems
Recap and Future Directions
Requirements
- Proficiency in Python and a solid grasp of fundamental machine learning principles
- Practical experience working with REST APIs or SDKs
- General familiarity with core Azure services
Target Audience
- Data scientists and ML engineers
- Application developers implementing AI-driven features
- Technical leads and solution architects
Testimonials (1)
the instructor :)
