https://github.com/ianhaggerty/final-capstone

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.
https://github.com/ianhaggerty/final-capstone

amazon data-analytics data-science data-visualization dataset matplotlib nlp nlp-machine-learning numpy pandas plotly reviews seaborn spacy tabulate textblob wordcloud

Last synced: 6 days ago
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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.

• Host: GitHub
• URL: https://github.com/ianhaggerty/final-capstone
• Owner: ianhaggerty
• Created: 2024-03-04T15:40:01.000Z (8 months ago)
• Default Branch: master
• Last Pushed: 2024-03-08T13:51:52.000Z (8 months ago)
• Last Synced: 2024-10-10T11:43:18.221Z (26 days ago)
• Topics: amazon, data-analytics, data-science, data-visualization, dataset, matplotlib, nlp, nlp-machine-learning, numpy, pandas, plotly, reviews, seaborn, spacy, tabulate, textblob, wordcloud
• Language: Jupyter Notebook
• Homepage: https://www.linkedin.com/in/ihaggerty/
• Size: 7.58 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# [Capstone Project](https://github.com/ianhaggerty/finalCapstone/tree/master) — [NLP Applications](https://medium.com/@mohamadhasan.sarvandani/top-applications-of-nlp-54834ca9c8ca)

## [CoGrammar](https://skills.cogrammar.com/) / [HyperionDev](https://www.hyperiondev.com/) / [Portfolio](https://www.hyperiondev.com/portfolio/IH23120012475/)

## Introduction

This repository represents the final capstone project in my _HyperionDev Data Science (Fundamentals)_ course. The main script can be found [here](https://github.com/ianhaggerty/finalCapstone/blob/master/sentiment_analysis.py) and corresponding

notebook [here](https://github.com/ianhaggerty/finalCapstone/blob/master/notebooks/sentiment_analysis.ipynb).

The objective of this project was to discover interesting and actionable insights within a dataset of [amazon reviews](https://www.kaggle.com/datasets/datafiniti/consumer-reviews-of-amazon-products).

[spaCy](https://spacy.io/usage) was used to conduct NLP analysis, in conjunction with

[TextBlob](https://textblob.readthedocs.io/en/dev/) to determine the sentiment and subjectivity.

Please see the [project requirements](https://github.com/ianhaggerty/finalCapstone/blob/master/reports/project_desc.pdf) and corresponding [report](https://github.com/ianhaggerty/finalCapstone/blob/master/reports/sentiment_analysis_report.pdf).

Offical grading, generously provided by Kenneth Mlimi, can be found [here](https://hyperiondev.cogrammar.com/review/acab9271caa0636a51999e66651876b5c291f15c631ac3141e313abae0620aa8/).

## Images

![Most dissimilar reviews.](images/dissimilar.png)

![Most similar reviews.](images/similar.png)

![Review similarity matrix.](images/matrix.png)

## Usage

1.  Setup the virtual environment.

    ```bash

    python -m venv venv

    ```

2.  Activate the virtual environment.

- Windows:

  ```shell

  venv\Scripts\activate

  ```

- Unix or MacOS:

  ```bash

  source venv/bin/activate

  ```

3. Install the requirements.

   ```bash

   pip install -r requirements.txt

   ```

4. Run the main script.

   ```bash

   python sentiment_analysis.py

   ```

   (Optional) run the notebook.

   ```bash

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

   ```

## A Note from the Author

Thanks for your interest! Please see my [GitHub](https://github.com/ianhaggerty) or [Linkedin](https://www.linkedin.com/in/ihaggerty/) to stay updated.