We welcome contributions to our documentation via GitHub pull requests, whether it’s fixing a typo or authoring an entirely new tutorial or guide. If you’re thinking about contributing documentation, please see How to Author Gensim Documentation.

Core Tutorials: New Users Start Here!

If you’re new to gensim, we recommend going through all core tutorials in order. Understanding this functionality is vital for using gensim effectively.

Tutorials: Learning Oriented Lessons

Learning-oriented lessons that introduce a particular gensim feature, e.g. a model (Word2Vec, FastText) or technique (similarity queries or text summarization).

How-to Guides: Solve a Problem

These goal-oriented guides demonstrate how to solve a specific problem using gensim.

Other Resources

Blog posts, tutorial videos, hackathons and other useful Gensim resources, from around the internet.

  • Use FastText or Word2Vec? Comparison of embedding quality and performance. Jupyter Notebook

  • Multiword phrases extracted from How I Met Your Mother. Blog post by Mark Needham

  • Using Gensim LDA for hierarchical document clustering. Jupyter notebook by Brandon Rose

  • Evolution of Voldemort topic through the 7 Harry Potter books. Blog post

  • Movie plots by genre: Document classification using various techniques: TF-IDF, word2vec averaging, Deep IR, Word Movers Distance and doc2vec. Github repo

  • Word2vec: Faster than Google? Optimization lessons in Python, talk by Radim Řehůřek at PyData Berlin 2014. Youtube video

  • Word2vec & friends, talk by Radim Řehůřek at 7.1.2015. Youtube video

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