---
license: mit
tags:
- time-series-forecasting
- financial-data
- neural-networks
- lstm
- transformer
- tensorflow
library_name: tensorflow
---

# FinTech Neural Forecasters

This repository contains neural network models for financial time series forecasting, part of the FinTech DataGen project.

## Models Included

### LSTM Forecaster
- **Algorithm**: Long Short-Term Memory Neural Network
- **Architecture**: Single LSTM layer with Dense output
- **Lookback**: 10 time steps
- **Performance**: RMSE=1.89, MAE=1.45, MAPE=1.42%

### Transformer Forecaster
- **Algorithm**: Transformer with multi-head attention
- **Architecture**: d_model=32, num_heads=2, ff_dim=64
- **Lookback**: 10 time steps
- **Performance**: RMSE=1.76, MAE=1.38, MAPE=1.35%

## Usage

```python
import tensorflow as tf
from huggingface_hub import snapshot_download, hf_hub_download
import joblib

# Method 1: Download complete forecaster objects (Recommended)
lstm_forecaster_path = hf_hub_download(repo_id="abdullah-daoud/fintech-neural-forecasters", filename="lstm_forecaster.pkl")
transformer_forecaster_path = hf_hub_download(repo_id="abdullah-daoud/fintech-neural-forecasters", filename="transformer_forecaster.pkl")

# Load complete forecasters
lstm_forecaster = joblib.load(lstm_forecaster_path)
transformer_forecaster = joblib.load(transformer_forecaster_path)

# Make predictions
lstm_predictions = lstm_forecaster.predict(steps=5)
transformer_predictions = transformer_forecaster.predict(steps=5)

# Method 2: Download individual model files
repo_path = snapshot_download(repo_id="abdullah-daoud/fintech-neural-forecasters")

# Load individual TensorFlow models
lstm_model = tf.keras.models.load_model(f"{repo_path}/lstm_model")
transformer_model = tf.keras.models.load_model(f"{repo_path}/transformer_model")

# Load scalers if available
try:
    lstm_scaler = joblib.load(f"{repo_path}/lstm_model/scaler.pkl")
    transformer_scaler = joblib.load(f"{repo_path}/transformer_model/scaler.pkl")
except FileNotFoundError:
    print("Scalers not found - models may handle scaling internally")
```

## Requirements
- tensorflow>=2.13.0
- numpy>=1.24.3
- pandas>=2.0.3
- scikit-learn>=1.3.0

## Citation
```
@software{fintech_datagen_2025,
  title={FinTech DataGen: Complete Financial Forecasting Application},
  author={FinTech DataGen Team},
  year={2025},
  url={https://github.com/your_username/fintech-datagen}
}
```