Text Summarization using Encoder-Decoder Model with TensorFlow and Keras

This project implements a text summarization algorithm using an Encoder-Decoder Model with TensorFlow and Keras. The project uses the news_summary dataset for training and evaluation.

Prerequisites

Before running the project, you need to install the following libraries:

• TensorFlow
• Keras
• NumPy
• Pandas
• NLTK

Usage

To run the code, execute the Untitled.ipynb file. This will open a Jupyter Notebook that includes all the necessary code to train and evaluate the model.

Results

The Encoder-Decoder Model architecture was implemented using TensorFlow and Keras. The model was trained and evaluated on the news_summary dataset.