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# Overview
This folder contains training and inference scripts for two models based on different technologies: MLP (multi-layer perceptron) using scikit-learn and an LSTM-based neural network using TensorFlow. Each model has its own folder with training and testing scripts. Developers interested in DGA detection in nDPI should also visit [this folder](../tests/dga) containing the original ML implementation.
The test scripts only show how to use an already-trained model.
## Requirements
To install the necessary dependencies, run
```bash
pip install -r requirements.txt
```
## How to use the scripts
### 1. scikit-learn (MLP model)
**Folder**: `scikit-learn_tests`.
#### Training
To train the MLP model, run the training script:
```bash
python scikit-learn_tests/training_script.py
```
#### Inference
After training, you can perform inference using the test script:
```bash
python scikit-learn_tests/test_script.py
```
### 2. TensorFlow (LSTM model)
**Folder**: `tensorflow_tests`.
#### Training
To train the LSTM model, run the training script
```bash
python tensorflow_tests/training_script.py
```
#### Inference
Once training is complete, you can run inference on the test set with
```bash
python tensorflow_tests/test_script.py
```
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