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GitHub repositories and users recommendations by embeddings
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GitHub repositories and users recommendations by embeddings


Using PyTorch-BigGraph (PBG) we train repo2vec (based on users stars) and user2vec models.


Visualizations with different kind of tensors (embeddings) are available at TensorBoard: [hope not to forget to update if it moves] Hints:

  • open from desktop browser (it fetch hundreds of MB for larger tensors and computations done on the client side!);
  • for better visual experience run T-SNE instead of PCA for 500-1K iterations on large tensors with 5-15 perplexity and learning rate set to 1 (from our experience); for smaller tensors you can play more due to fewer computations (but losing in data points);
  • you may choose feature to be colored by (language for repos, type for users, etc.)

To run our pipeline

  1. Change resources/config.template.json to resources/config.json with your info;
  2. Run notebook;
  3. Download SQL dump you like (here we use 2019-06-01) at data/ folder and extract relationships tables (CSV): followers.csv, watchers.csv, project_members.csv; and metadata: users.csv, projects.csv to data/%Y-%m-%d folder (or change directories code dependencies at notebooks);
  4. View tb/README for more info about TensorBoard launch with your embeddings and metadata (docker based, but it is easy to run without it if needed);
  5. Modify code the way you like to find some new insights and share with us! s


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