This repository is devoted to the exploration and implementation of various Natural Language Processing (NLP) techniques for Named Entity Recognition (NER). Named Entity Recognition is a key task in the field of NLP, aimed at identifying and categorizing key elements in text into predefined categories such as names of persons, organizations, locations, expressions of times, quantities, monetary values, percentages, etc.
The repository contains the CRF, FastText, Random Forest, LSTM and CNN models for NER, demonstrating the efficiency and effectiveness of various machine learning methods in NLP.
The project is open-source and available under the MIT License.