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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.


Running the Word2Vec Tutorial Notebook

  1. From the command line, first, clone this repo.
    git clone <this repo url>
  2. Next, switch to the word2vec directory of this repo.
    cd  nlp-in-practice/word2vec
  3. Then, run jupyter notebook
    jupyter notebook
  4. Select Word2Vec.ipynb, sip a cup of coffee and enjoy! You can now re-run the cells.