Introduction

Why FENN?

• Auto-Configuration: yaml files are automatically parsed and injected into your entrypoint, so you avoid hardcoded hyperparameters.

• Instant Logging: All print statements and configurations are captured to local logs and compatible remote trackers.

• Remote Monitoring: Native integration with Weights & Biases (WandB) lets you monitor experiments from anywhere.

Tip

If you are using FENN for the first time, start with the Quickstart section to scaffold a project, configure your first fenn.yaml, and run an experiment end-to-end in a few minutes.

Roadmap

🚀 High Priority

High-priority goals include richer documentation, safer key management (for example, through .env support), and multiple or layered YAML configurations.

• Documentation: Write comprehensive documentation and examples.

🔮 Planned Features

Planned features include ML project templates, model utilities, notification tools, data exploration helpers, analysis utilities (such as confusion matrices), additional integrations like TensorBoard, and comprehensive testing support.

• ML Templates: Automated creation of standard project structures.

• Model Tools: Utilities for Neural Network creation, training, and testing.

• Notifications: Email notification system for completed training runs.

• Data Tools: Data exploration and visualization helpers.

• Analysis: Result analysis tools (diagrams, confusion matrices, etc.).

• Integrations: Support for TensorBoard and similar tracking tools.

• Testing: Comprehensive unit and integration tests for the framework.