Regression-models

Table of Contents

1. About The Project
   • Built With
2. Getting Started
   • Installation
3. Usage
4. Contact
5. Acknowledgments

About The Project

This repository contains projects including: simple linear reggression on insurance data, multiple linear regression based on the diabetes dataset as well as on an hourlywage dataset, and logistic regression on the iris dataset. All of these were created on Visual Studio Code using Jupyter Notebook.

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Built With

• Python
• JupyterNotebook
• VisualStudioCode

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Getting Started

To get a local copy up and running follow these simple example steps.

Installation

1. Ensure you have the latest python program installed from: python.org/downloads/. Note these programs were made using Jupyter notebook.
2. Clone the repository

   git clone https://github.com/EstherSlabbert/Regression-models.git

3. Install numpy, pandas, seaborn, sklearn packages

   py -m pip install {insert package name here}

4. Install jupyter notebook: https://jupyter.org/install

   py -m pip install notebook

5. Run program(s) as you see fit. I used Visual Studio Code which can be found here: https://code.visualstudio.com/download.

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Usage

This project includes examples of code for simple linear regression, multiple linear regression, and logistic regression from different datasets and can be used as a guide on which to base your own regression models.

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Contact

Esther Slabbert - [email protected]

Project Link: https://github.com/EstherSlabbert/Regression-models

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Acknowledgments

• HyperionDev Data Science Bootcamp task assignments.

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