Skip to content
Tool for exploring Word Vector models
Branch: master
Clone or download
Dominiek Ter Heide
Dominiek Ter Heide Updated todo
Latest commit 6770425 Mar 10, 2016
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
public
ui
.gitignore
LICENSE
README.md
explore Moved app.py to a ./explore command Mar 9, 2016
explorer.py
package.json Made JS code StandardJS compliant Mar 9, 2016
requirements.txt

README.md

Word2Vec Explorer

This tool helps you visualize, query and explore Word2Vec models. Word2Vec is a deep learning technique that feeds massive amounts of text into a shallow neural net which can then be used to solve a variety of NLP and ML problems.

Word2Vec Explorer uses Gensim to list and compare vectors and it uses t-SNE to visualize a dimensional reduction of the vector space. Scikit-Learn is used for K-Means clustering.

The UI is built using React, Babel, Browserify, StandardJS, D3 and Three.js.

TSNE 10K

TSNE Labels

Vector Comparisons

Setup

To install all Python depenencies:

pip install -r requirements.txt

Usage

Load the explorer with a Word2Vec model:

./explore GoogleNews-vectors-negative300.bin

Now point your browser at localhost:8080 to load the explorer!

Obtaining Pre-Trained Models

A classic example of Word2Vec is the Google News model trained on 600M sentences: GoogleNews-vectors-negative300.bin.gz

[More pre-trained models]](https://github.com/3Top/word2vec-api#where-to-get-a-pretrained-models)

Development

In order to make changes to the user interface you will need some NPM dependencies:

npm install
npm start

The command npm start will automatically transpile and bundle any code changes in the ui/ folder. All backend code can be found in explorer.py and ./explore.

Before submitting code changes make sure all code is compliant with StandardJS as well as Pep8:

standard
pep8 --max-line-length=100 *.py explore

Todo

  • 3D GPU/WebGL view (on branch 3d)
  • Make sure axes stay when zooming/panning scatterplot
  • Autocomplete in query interface
  • Look into supporting other high dimensional data models (go beyond word vectors)
  • Drill-down of vector that shows real distance between neighbors
  • Improved sample rated view that takes into account term counts and connectedness
You can’t perform that action at this time.