Text Classification Using Neural Networks

This repository contains a Python script for classifying text data using deep learning models in TensorFlow and Keras. The script utilizes natural language processing techniques, such as stemming and stop-word removal, and applies TF-IDF vectorization to prepare text data for classification.

Project Overview

The script performs the following operations:

1. Pre-processing: Text data is stemmed and cleaned of stop words to reduce noise and dimensionality.
2. Vectorization: The cleaned text is converted into a numeric form using TF-IDF vectorization.
3. Model Training: A neural network model is trained using the vectorized text data.
4. Evaluation: The model is evaluated using the F1 score, precision, and recall metrics.
5. Execution Time: The script tracks the total execution time.

Prerequisites

To run this script, you need the following libraries installed:

• pandas
• numpy
• scikit-learn
• nltk
• TensorFlow
• Keras

You can install these packages via pip:

pip install pandas numpy scikit-learn nltk tensorflow keras