nlp-in-practice

nlp-in-practice

kavgan

Starter code to solve real world text data problems. Includes: Gensim Word2Vec, phrase embeddings, Text Classification with Logistic Regression, word count with pyspark, simple text preprocessing, pre-trained embeddings and more.

nlp machine-learning natural-language-processing
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1.2k Stars
790 Forks
1.2k Watchers
Jupyter Notebook Language
Cost to Build
$690.3K
Market Value
$2.88M
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Growth over time

12 data points  ·  2021-08-01 → 2025-08-01
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What is the kavgan/nlp-in-practice GitHub project? Description: "Starter code to solve real world text data problems. Includes: Gensim Word2Vec, phrase embeddings, Text Classification with Logistic Regression, word count with pyspark, simple text preprocessing, pre-trained embeddings and more.". Written in Jupyter Notebook. Explain what it does, its main use cases, key features, and who would benefit from using it.

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