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In this video, we delve into the powerful capabilities of Gensim's Word Mover's Distance (WMD) for measuring semantic similarity between texts. However, calculating WMD can be computationally intensive, especially with large datasets. Join us as we explore how to leverage Python's multiprocessing to significantly speed up these calculations, making your text analysis more efficient and effective. Whether you're a data scientist or a machine learning enthusiast, this tutorial will equip you with the tools to optimize your workflow.

Today's Topic: Speed Up Gensim WMD Similarity with Multiprocessing in Python

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jxn (https://stackoverflow.com/users/28009...
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Imdat Solak (https://stackoverflow.com/users/82091...)

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