kavgan/nlp-in-practice
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.
This project provides practical code examples and tools to help you analyze and understand large amounts of text. You can feed in documents, articles, or other textual data, and it will help you extract key phrases, summarize topics, classify content, or visualize important words. This is designed for data analysts, researchers, or anyone who needs to make sense of unstructured text.
1,183 stars. No commits in the last 6 months.
Use this if you need to process and gain insights from text data, such as identifying important keywords, classifying documents, or preparing text for further analysis.
Not ideal if you are looking for a ready-to-use, off-the-shelf application with a graphical interface for text analysis.
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Dec 02, 2020
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