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Duration 14 hours
Course Outline
Foundations of Azure Machine Learning
- Survey of AML capabilities and underlying architecture
- Walkthrough of a comprehensive end-to-end workflow within AML (Azure ML pipelines)
- Exploring the Azure Machine Learning Studio interface
Data Processing and Model Development
- Preparing data for analysis
- Constructing a predictive model
- Training and validating the model
Assessing Model Performance and Stability
- Selecting appropriate validation metrics for ML models
- Mitigating and avoiding overfitting
Model Governance and Release
- Registering trained models
- Generating model images
- Executing model deployment
Basics of the OpenAI API on Azure
- Introduction to the OpenAI API ecosystem
- Configuring API settings and managing authentication
Retrieval Mechanisms and App Integration
- Leveraging AI Search for document retrieval
- Integrating OpenAI models into application architecture
Adaptive Techniques and Production Standards
- Model fine-tuning and customization
- Adhering to best practices in production environments
Conclusions and Future Directions
Requirements
- Proficiency in Python and foundational machine learning principles
- Practical experience with REST APIs or Software Development Kits (SDKs)
- General familiarity with the Azure service ecosystem
Intended Audience
- Data scientists and ML engineers
- Application developers implementing AI capabilities
- Technical leads and solution architects
Testimonials (1)
the instructor :)
