Sentence Auto-Completion Using NLP

Overview

This project implements a Sentence Auto-Completion model using Natural Language Processing techniques. The model predicts the next word in a sequence based on the input context. It is built using TensorFlow and Keras and trained on a large text corpus.

Features

• Text cleaning to preprocess the input data.
• Tokenization of text to convert words into numerical representations.
• Generation of n-grams for training the model.
• LSTM architecture for handling sequence prediction tasks.

Technologies Used

• Python
• TensorFlow
• Keras
• NLTK
• NumPy
• Pandas

Installation

Prerequisites

Ensure you have Python 3.x installed. It is recommended to use a virtual environment.

Install Required Libraries

You can install the required libraries using pip:

pip install tensorflow nltk pandas numpy