xl3ehindtim / word-embeddings

Word embedding vector space visualization

Word Embeddings

This repository contains pre-generated word embeddings for Word2Vec using Google-news-300, spaCy (NLP), TF-IDF and CountVectorizer. For each of these methods a 2D vector space has been created using the following word list: ['Artist', 'Musician', 'Detective', 'Birch', 'Water', 'War', 'Programmer', 'Gardener', 'Ocean', 'Lake', 'Teacher', 'Doctor', 'Job', 'River', 'Triathlon', 'Oak', 'Horse', 'Cyclist', 'Painting', 'Swimmer', 'Writer', 'Cat', 'Dog', 'Animal', 'Chef', 'Firefighter', 'Clothing', 'Engineer', 'Architect', 'Dancer', 'Conflict', 'Hiker', 'Drummer', 'Elm', 'Cow', 'Painter', 'Sculptor', 'Botanist', 'Zoologist', 'Historian', 'Strife', 'Shirt', 'Sweater', 'Marathon']

The resulting pyplot figures are located in /result