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Undergraduate Data Science project for small businesses, covering data-driven solutions for optimizing operations, increasing efficiency, and driving growth. Includes descriptive, predictive, and prescriptive analytics, machine learning, and decision strategies.

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Data Science Project for Small Businesses

This repository contains an undergraduate Data Science project aimed at the world of small businesses. The project offers a comprehensive analysis of data-driven solutions to optimize operations, increase efficiency, and drive growth for small businesses.

Contents

  • Descriptive Analysis: Explore insights from small business data, uncovering trends and patterns.

  • Predictive Analysis: Implementation of Machine Learning models to predict outcomes and make informed decisions.

  • Prescriptive Analysis: Optimization strategies and personalized recommendations to enhance operations.

  • Data Visualization: Informative charts and visualizations to effectively communicate results.

How to Use

To make the most of this project, follow these steps:

  1. Clone this repository to your local environment.
  2. Explore the notebooks and scripts in each directory for details on the analysis performed.
  3. Customize and apply the techniques to your own small business scenario.

Requirements

  • Python 3.x
  • Data Science Libraries (Pandas, NumPy, Scikit-Learn, Matplotlib, etc.)

Contributions

Contributions are welcome! Feel free to open issues or submit pull requests.

License

This project is licensed under the MIT License. See the LICENSE file for more details.


We hope this Data Science project proves useful for improving the operations and growth of small businesses. Happy data exploration!

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Undergraduate Data Science project for small businesses, covering data-driven solutions for optimizing operations, increasing efficiency, and driving growth. Includes descriptive, predictive, and prescriptive analytics, machine learning, and decision strategies.

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