Great idea, thank you for your feedback! I generated embeddings for repositories using a SVC model trained on a dataset containing almost all stars of Github. Recommendations are produced by finding the nearest neighbors in the resulting vectorial space. I might be improving this even further by including forks and watcher data in the future, but it's becoming expensive to train