Practical Tutorials

Welcome to the hands-on section of the HydraFlow documentation. These tutorials provide practical examples to help you understand how HydraFlow works in real-world scenarios.

What You'll Learn

These tutorials demonstrate the core capabilities of HydraFlow through executable examples:

1. Basic Application - Create and run a simple HydraFlow application
2. Automated Workflows - Define and execute complex experiment workflows
3. Results Analysis - Load, filter, and analyze experiment results

Each tutorial includes:

• Complete working code examples
• Step-by-step explanations
• Real command outputs
• Practical insights

Prerequisites

To follow these tutorials, you'll need:

• HydraFlow installed (Installation Guide)
• Basic understanding of Python
• Familiarity with machine learning experiment concepts

Learning Path

These tutorials are designed to be followed in sequence:

• Basic Application Learn how to create and run a simple HydraFlow application
• Automated Workflows Define complex experiment workflows using hydraflow.yaml
• Results Analysis Analyze experiment results using HydraFlow's powerful APIs

By working through these tutorials, you'll gain a practical understanding of HydraFlow's capabilities and how it can streamline your machine learning experiments.

Next Steps

After completing these tutorials, you'll be ready to:

• Explore the detailed User Guide for in-depth explanations
• Apply HydraFlow to your own machine learning projects
• Customize HydraFlow's components for your specific needs