Project Name: Information Extraction and Grouping (NLP) Description The Information Extraction and Grouping project is an NLP-based solution designed to extract text from photos and extract relevant information using Named Entity Recognition (NER) techniques. The project aims to automate the process of extracting valuable data from images, making it easier for users to analyze and organize textual information.

Key Features Text Extraction from Photos: The project utilizes optical character recognition (OCR) techniques to extract text from images and convert it into machine-readable format. Information Extraction: The extracted text is processed using natural language processing techniques to identify relevant information such as names, locations, dates, organizations, etc. Named Entity Recognition (NER): NER algorithms are employed to recognize and classify named entities within the extracted text. This helps in grouping similar entities together for further analysis. Data Grouping: The project employs advanced algorithms to group extracted information based on the identified named entities, facilitating effective organization and categorization of data. User-Friendly Interface: The project provides a user-friendly interface where users can upload images, view the extracted text, and explore the grouped information.