Overview

This project implements a Convolutional Neural Network (CNN) for text classification using TensorFlow and Keras. The model classifies text descriptions into multiple categories with attention to class imbalance.

Features

• Text preprocessing: tokenization and padding

• CNN architecture with Embedding, Conv1D, and GlobalMaxPooling layers

• Handling imbalanced datasets using class weights

• Training and validation performance visualization

• Classification report and confusion matrix for model evaluation

• Requirements

To run this project, make sure you have Python 3.7 or higher installed. The following Python libraries are required:

• pandas
• numpy
• scikit-learn
• tensorflow (2.x)
• matplotlib
• seaborn