Models
Cloudera AI Project Lifecycle
Managing Models
Models - Concepts and Terminology
Challenges with Machine Learning in production
Challenges with model deployment and serving
Challenges with model monitoring
Challenges with model governance
Model visibility
Model explainability, interpretability, and reproducibility
Model governance using Apache Atlas
Creating and deploying a Model
Hosting an LLM as a Cloudera AI Workbench model
Deploying the Cloudera AI Workbench model
Usage guidelines for deploying models with Cloudera AI
Known Issues and Limitations with Model Builds and Deployed Models
Request/Response Formats (JSON)
Testing calls to a Model
Securing Models
Access Keys for Models
API Key for Models
Enabling authentication
Generating an API key
Managing API Keys
Workflows for active Models
Technical metrics for Models
Debugging issues with Models
Deleting a Model
Example - Model training and deployment (Iris)
Training the Model
Deploying the Model