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LSTM Text Classification - A Simple LSTM Example

This project implements a text classification model using Long Short-Term Memory (LSTM) neural networks.

Project Structure

libraries.py: Contains the import statements for required libraries.
preprocessing.py: Includes data loading and preprocessing steps.
model.py: Defines the LSTM model architecture.
train.py: Contains the code for training the model.
evaluate.py: Evaluates the trained model on the test data.

How to Run

Install the required dependencies:
```
pip install -r requirements.txt
```
Run the preprocessing script to prepare the data:
```
python preprocessing.py
```
Define and compile the model:
```
python model.py
```
Train the model:
```
python train.py
```
Evaluate the model:
```
python evaluate.py
```

or

Run the run.py script to execute everything in order:
```
python run.py
```

Requirements

The project dependencies are listed in requirements.txt.