E-LIBRARY WITH URLS TUTORIAL,PDF BOOKS & VIDEOS USING MACHINE LEARNING

Abstract

The AI-powered E-Library is an intelligent platform designed to store, categorize, and recommend educational resources such as URLs, tutorial PDFs, and videos using Machine Learning techniques. The system leverages Natural Language Processing (NLP) to classify content into various academic domains, enabling users to easily find relevant materials. A recommendation engine powered by Collaborative Filtering and Content-Based Filtering suggests personalized resources based on user interests and browsing history. Additionally, a semantic search engine enhances discoverability by allowing users to search using natural language queries. The platform also incorporates text summarization and keyword extraction features, ensuring that users can quickly grasp key insights from lengthy materials. By integrating an intuitive frontend (React.js/Angular) with a robust backend (Flask/Django) and database storage (MongoDB/PostgreSQL), the system offers a seamless digital learning experience. Moreover, resources are stored securely on cloud services like Google Drive, AWS S3, or Firebase, providing easy accessibility. The platform can be further enhanced with features such as voice-based search, chatbot assistance, and integration with external digital libraries (Google Scholar, IEEE Xplore, etc.) to create a truly comprehensive AI-driven educational ecosystem.