# 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
```