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  1. NLP-sentence-encoders NLP-sentence-encoders Public

    Highlights trade-offs and optimizations to take into account when using sentence encoder models to predict essay scores.

    Jupyter Notebook

  2. NLP-spelling-mistake-feature-engineering NLP-spelling-mistake-feature-engineering Public

    Experiments with different methods in an attempt to create a more accurate spelling mistake ML feature.

    Jupyter Notebook

  3. NLP-unique-words-feature-engineering NLP-unique-words-feature-engineering Public

    Shows how a negative correlation between unique words and essay scores is actually due to spelling mistakes.

    Jupyter Notebook

  4. NLP-initial-feature-engineering NLP-initial-feature-engineering Public

    A notebook showing that a number of simple ML features can be extracted from text data before using more advanced techniques.

    Jupyter Notebook

  5. NLP-punctuation-feature-engineering NLP-punctuation-feature-engineering Public

    Demonstrates how careful selection can be more useful than including everything when making a punctuation feature.

    Jupyter Notebook

  6. NLP-TF-IDF NLP-TF-IDF Public

    Outlines a series of optimization experiments to take into account when using TF-IDF to predict essay scores.

    Jupyter Notebook