NLP Tools and API Project

This repository features implementations of advanced Natural Language Processing (NLP) techniques designed to make textual analysis simple and efficient. The project integrates core NLP methods like TF-IDF, Cosine Similarity, and VADER Sentiment Analysis with FastAPI to provide accessible, high-performance APIs.

Overview

Natural Language Processing is a cornerstone for various applications such as search engines, recommendation systems, and sentiment analysis. This project focuses on building intuitive tools for text processing and analysis using Python, combined with a robust API structure via FastAPI.

Core Features • TF-IDF (Term Frequency-Inverse Document Frequency) Measure the importance of a term in a document concerning a collection of documents. Essential for information retrieval and text mining tasks. • Cosine Similarity A mathematical approach to calculate the similarity between text documents, providing insights into their contextual alignment. • VADER Sentiment Analysis An efficient rule-based sentiment analysis model optimized for social media text, evaluating positivity, negativity, and neutrality in expressions. • API Endpoints with FastAPI Fast and secure RESTful APIs offering NLP functionalities, equipped with automatic Swagger documentation for seamless interaction.

Why Use This Repository?

This project combines essential NLP tasks with scalable API solutions, making it ideal for both beginners and advanced developers: • Simplicity: Well-documented and easy-to-understand implementation of key NLP concepts. • Performance: FastAPI ensures high-speed processing and minimal latency for API calls. • Flexibility: Modular design allows easy integration into your applications. • Real-World Application: Solutions tailored for real-world text analysis challenges, like sentiment analysis in user feedback or content similarity for recommendation systems.

Technology Stack • Programming Language: Python • Framework: FastAPI for API development • Libraries: • Scikit-learn: For TF-IDF and similarity calculations • VADER: For sentiment analysis • Uvicorn: For serving the FastAPI application

Applications 1. Sentiment Analysis: Quickly gauge public sentiment on social media or analyze customer feedback. 2. Search and Recommendations: Build search engines and recommendation systems using similarity measures. 3. Content Analysis: Identify patterns and insights from textual data for research or marketing.

Contributing

Contributions to enhance features or add new capabilities are warmly welcomed. Please open an issue or submit a pull request with your suggestions or fixes.

Contact

If you have questions, feedback, or feature requests, feel free to reach out: • Name: Aparna • Email: aparnasingha3003@gmail.com • GitHub: Aparna-Singha

License

This project is licensed under the MIT License, allowing open collaboration and use.