Gensim is a powerful Python library for topic modeling, document similarity, and other NLP tasks. It's widely used for word2vec, fastText, and TF-IDF implementations. Here's a quick guide to its core features:

🔧 Key Features

  • Efficient Algorithms: Optimized for large-scale text data processing
  • Pre-trained Models: Access models like word2vec and doc2vec
  • Integration: Works seamlessly with scikit-learn and spaCy
  • Flexibility: Customizable for various NLP applications

📌 Example Use Cases

  • Semantic Similarity: Compare documents using cosine similarity
  • Topic Modeling: Discover hidden themes in a corpus
  • Text Vectorization: Convert text into numerical vectors

🌐 Explore More

For hands-on tutorials and advanced topics, check our Gensim Documentation.

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