Neural Network Implementation with JAX

A complete implementation of a neural network using JAX, featuring:

• Custom MLP architecture
• Training/validation metrics tracking
• Interactive visualizations
• Synthetic data generation

📊 Performance Results

Final Epoch Metrics

Metric	Training	Validation
Loss	0.0335	-
Accuracy	99.80%	98.50%

Training Progress

Epoch 0 | Train Loss: 0.4550 | Train Acc: 81.50% | Val Acc: 96.00%
Epoch 1 | Train Loss: 0.1815 | Train Acc: 96.80% | Val Acc: 98.00%
...
Epoch 9 | Train Loss: 0.0335 | Train Acc: 99.80% | Val Acc: 98.50%

🛠️ Technical Stack

• Core Framework: JAX 0.4.13
• Optimization: Optax 0.1.7
• Visualization: Matplotlib 3.7.1
• Metrics: scikit-learn 1.3.2

📂 Project Structure

src/ ├── train.py # Main training script ├── model.py # MLP architecture ├── data_loader.py # Synthetic dataset ├── metrics.py # Accuracy/loss calculations └── visualize.py # Plot generation

🚀 Getting Started

1. Install Dependencies

pip install -r requirements.txt

2. Run Training

python src/train.py

3. View Results

• training_metrics.png: Loss/accuracy curves

• predictions.png: Model predictions vs true labels

🔍 Key Features

• Modular Design: Separate components for easy modification
• Reproducible: Fixed random seeds
• Visual Diagnostics: Clear performance tracking

📈 Interpretation

• The model achieves 99.8% training accuracy and 98.5% validation accuracy
• Rapid convergence in first 3 epochs (see loss curve)
• Minimal overfitting (small train-val accuracy gap)

🤝 Contributing

Pull requests welcome! For major changes, please open an issue first.

📜 License

Key Features of This README:

1. Visual Integration: Embeds your actual result images
2. Performance Highlights: Shows key metrics prominently
3. Structured Layout: Clear sections for setup, results, and technical details
4. Reproducibility: Includes exact package versions
5. Professional Formatting: Tables and code blocks for readability

To use:

1. Save as README.md in your project root
2. Commit to GitHub:

   git add README.md
   git commit -m "Add comprehensive project documentation"
   git push