GitHub / chizeni24 / Medical-Search-Engine
The project focuses on developing medical word embeddings using Word2vec and FastText in Python to create a search engine and Streamlit UI. The use of embeddings helps overcome the challenges of extracting context from text data, making it easier to represent words as semantically meaningful dense vectors.
JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/chizeni24%2FMedical-Search-Engine
PURL: pkg:github/chizeni24/Medical-Search-Engine
Stars: 0
Forks: 0
Open issues: 0
License: None
Language: Jupyter Notebook
Size: 32.9 MB
Dependencies parsed at: Pending
Created at: over 2 years ago
Updated at: about 2 years ago
Pushed at: about 2 years ago
Last synced at: about 2 years ago
Topics: fasttext-embeddings, medical-application, pca-analysis, skipgram, word2vec-embeddinngs