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This represents the final capstone project in my HyperionDev Data Science (fundamentals) course. A dataset of Amazon customer reviews is analysed using natural language processing.

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Introduction

This repository represents the final capstone project in my HyperionDev Data Science (Fundamentals) course. The main script can be found here and corresponding notebook here.

The objective of this project was to discover interesting and actionable insights within a dataset of amazon reviews.

spaCy was used to conduct NLP analysis, in conjunction with TextBlob to determine the sentiment and subjectivity.

Please see the project requirements and corresponding report.

Offical grading, generously provided by Kenneth Mlimi, can be found here.

Images

Most dissimilar reviews. Most similar reviews. Review similarity matrix.

Usage

  1. Setup the virtual environment.

    python -m venv venv
  2. Activate the virtual environment.

  • Windows:

    venv\Scripts\activate
  • Unix or MacOS:

    source venv/bin/activate
  1. Install the requirements.

    pip install -r requirements.txt
  2. Run the main script.

    python sentiment_analysis.py

    (Optional) run the notebook.

    jupyter nbconvert --execute --to notebook --inplace notebooks/sentiment_analysis.ipynb

A Note from the Author

Thanks for your interest! Please see my GitHub or Linkedin to stay updated.

About

This represents the final capstone project in my HyperionDev Data Science (fundamentals) course. A dataset of Amazon customer reviews is analysed using natural language processing.

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