Models
Models
Introduction to Production Machine Learning
Concepts and Terminology
Engines for Experiments and Models
Snapshot Code
Build Image
Run Experiment / Deploy Model
Creating and Deploying a Model (QuickStart)
Calling a Model
Updating Active Models
Re-deploy an Existing Build
Deploy a New Build for a Model
Stop a Model
Restart a Model
Securing Models using Model API Key
Enabling Authentication
Generating a Model API Key
Managing Model API Keys
Enabling Model Metrics
Tracking Model Metrics
Usage Guidelines
Model Code
Model Artifacts
Resouce Consumption and Scaling
Security Considerations
Deployment Considerations
Model Training and Deployment - Iris Dataset
Create a Project
Train the Model
Deploy the Model
Model Monitoring and Administration
Monitoring Individual Models
Monitoring All Active Models
Deleting a Model
Disabling the Models Feature
Debugging Issues with Models
Building
Pushing
Deploying
Deployed