Models
Managing Models
Models overview
Models - Concepts and Terminology
Cloudera AI Project Lifecycle
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
Configuring model metrics payload limit
Example - Model training and deployment (Iris)
Training the Model
Deploying the Model
Model Governance
Enabling model governance
ML Governance Requirements
Registering training data lineage using a linking file
Viewing lineage for a model deployment in Atlas
Model Metrics
Enabling model metrics
Tracking model metrics without deploying a model
Tracking metrics for deployed models
Using Registered Models
Deploying a model from Registered Models
Viewing details of a registered model
Editing model visibility
Deleting a registered model version