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Introduction

What is JFrog ML?
JFrog ML Architecture

Quickstart

Installation
Getting Started
JFrog ML Examples

BUILD Models

Model Build Overview
Training Models
Testing Models
- Local Testing
- Adding Integration Tests to a Model Build
Loading Pre-built Models
Model Registry and Metadata
Advanced Build Concepts

Serve Models

Prediction Input & Output Adapters
Real-Time Deployments
Batch Deployments
Streaming Deployments
Inference Analytics
LLM Model Library

Monitor Models

Runtime Metrics
Model Monitors
Prediction Timers
Performance Monitors
Inference Distribution (Analytics)

Automate

Defining Automations
- Automating Build & Deploy
- Automating Batch Execution
Managing Automations
Automation Tutorials
- Scheduled Training and Deployment
- Monitoring Batch Execution Failures
Github Actions
- Build & Deploy Actions
- Advanced CI/CD Patterns

Configuration

Alerts
Instance Sizes & ML Credits
JFrog Platform
Account Management
Secret Management
Accessing AWS Resources with IAM Role

Model EXPERIMENTation

Integrating Experiment Tracking Tools with JFrog ML

Feature Store

Feature Store Overview
Quickstart Guide
Data Sources
- Batch Data Sources
- Streaming Data Sources
Batch Feature Set
Streaming Feature Set
Feature Consumption
- Features in Inference
- Features in Training
Feature Set Alerts
Use-cases
Cross-environment Online Serving Replication

Prompt Management

Managing Prompts
AI Providers

Qwak Client

Qwak Client Examples

TROUBLESHOOTING

Performance Issues
Installation Issues
Network & Connectivity Issues

Changelog

Qwak-SDK
A Migration Guide for the new SDK - v0.5

Github Actions

Automate your ML models lifecycle using GitHub Actions

Updated 6 months ago

What’s Next

Automate JFrog ML Build and Deploy with Github Actions.

Build & Deploy Actions
Advanced CI/CD Patterns