Skip to content

index.md

Latest commit

 

History

History
112 lines (79 loc) · 2.98 KB

index.md

File metadata and controls

112 lines (79 loc) · 2.98 KB
Raw

AstroML Documentation

Welcome to the AstroML documentation!

🚀 Quick Start

AstroML is a comprehensive machine learning framework for the Stellar network, providing tools for:

  • Graph Machine Learning: Advanced GNN models for transaction analysis
  • Fraud Detection: Sophisticated algorithms for identifying suspicious activity
  • Feature Engineering: Comprehensive feature extraction and processing
  • Data Ingestion: Real-time Stellar ledger data processing

📚 Documentation Sections

Machine Learning

Configuration & Experiments

Performance & Scaling

Deployment

API Reference

🔧 Installation

# Clone the repository
git clone https://github.com/tecch-wiz/astroml.git
cd astroml

# Create virtual environment
python3 -m venv venv
source venv/bin/activate

# Install dependencies
pip install -r requirements.txt

# For documentation only
pip install -r docs/requirements.txt

🎯 Quick Examples

Running Experiments with Hydra

# Basic experiment
python train.py

# Override parameters
python train.py training.lr=0.001 model.hidden_dims=[128,64]

# Use pre-configured experiments
python train.py --config-name experiments/debug
python train.py --config-name experiments/baseline

Docker Deployment

# Build and run all services
docker-compose up -d

# Run specific services
docker-compose up postgres redis
docker-compose up ingestion

📊 Features

Machine Learning

  • Graph Neural Networks: GCN, GraphSAGE, GAT implementations
  • Structural Analysis: Centrality measures, importance metrics
  • Temporal Modeling: Time-series analysis for transaction patterns

Data Processing

  • Real-time Ingestion: Stellar ledger streaming
  • Feature Engineering: Automated feature extraction
  • Data Validation: Quality checks and integrity verification

Deployment

  • Docker Support: Multi-stage builds for different environments
  • Configuration Management: Hydra-based experiment tracking
  • Monitoring: Comprehensive logging and metrics

🔗 Links

📖 Contributing

We welcome contributions! Please see our Contributing Guide for details.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.