Next Word Prediction Project

This Next Word Prediction project leverages advanced machine learning techniques and web technologies to provide real-time word prediction. Developed in May 2022, this project showcases the integration of various tools and frameworks to achieve high accuracy and seamless deployment.

Key Features

LSTM-Based Sequential Model

The core of this project is a Sequential model with a focus on Long Short-Term Memory (LSTM). This model architecture significantly improves the accuracy of next-word predictions, achieving a remarkable 97%.

Flask Deployment

To make the model accessible and provide real-time responses, the model is deployed using Flask. This lightweight WSGI web application framework allows for easy and efficient deployment of machine learning models.

Real-Time Response with Ajax

The project employs Ajax for asynchronous web requests, ensuring that users receive real-time predictions without the need to reload the page. This is achieved through seamless integration with jQuery.

Data Handling with Pandas and Pickle

Pandas is used for efficient data manipulation and preprocessing. The trained model is serialized using Pickle, allowing for easy storage and loading of the model.

Containerization with Docker

The entire application is containerized using Docker, ensuring that the setup is portable and can be easily replicated across different environments. Docker simplifies the deployment process and enhances the scalability of the application.

Technical Details

• Language: Python
• Framework: Flask
• Frontend: Ajax, jQuery
• Machine Learning: Sequential model with LSTM
• Data Handling: Pandas, Pickle
• Containerization: Docker

Experience the efficiency and accuracy of a state-of-the-art next-word prediction model. This project demonstrates the powerful combination of machine learning and web technologies to deliver a smooth and responsive user experience.

Get started today and explore the capabilities of next-word prediction!