Next Word Predictor
Overview
This project is an AI-powered text prediction system that suggests the next word in a given sentence using deep learning techniques. It leverages natural language processing (NLP) and machine learning models to enhance text generation capabilities. The project can be used in chatbots, search engines, and auto-complete applications.
Objective
The objective of this project is to develop an intelligent Next Word Prediction system that enhances text input efficiency using natural language processing (NLP) and deep learning. The model is designed to understand the context of a given sentence and accurately predict the next word, improving the user experience in applications like chatbots, search engines, and text autocompletion tools. By leveraging TensorFlow/Keras for model training and Streamlit for deployment, this project provides an interactive and real-time word prediction system. The focus is on optimizing text processing, improving model accuracy through data preprocessing and training, and showcasing a practical application of AI-driven language modeling. Additionally, this project serves as a stepping stone for implementing advanced NLP models like LSTM, Transformer-based architectures (BERT, GPT), or RNNs for better performance in future iterations.
Project Workflow
1 . Data Collection & Cleaning :- Loads a CSV file containing text data.
- Prepares data using text preprocessing techniques.
- Uses deep learning models (possibly an LSTM or Transformer).
- Converts text into numerical representations (word embeddings).
- Trains the model on sequences of words to predict the next word.
- Provides a simple UI where users input a sentence.
- The model suggests the next word dynamically.
- The Streamlit app allows users to interact with the model in real-time.