Data Science Project Repository

Project Overview

• Comprehensive guide for anyone interested in learning and applying data science from scratch.

Table of Contents

1. Introduction
2. Getting Started
   • Prerequisites
   • Installation
3. Project Structure
4. Notebooks
5. Machine Learning Projects
   • Random Forest
   • Logistic Regression
   • Bayes Theory
   • Decision Tree
   • Convolutional Neural Networks (CNN)
6. Dataset
7. Contributing
8. License

Introduction

Data Science is essentially the study of data. We will be transforming raw data into valuable insights and actionable information.

Getting Started

Prerequisites

Ensure you have the following prerequisites installed:

• Python (version 3.12)
• Jupyter Notebooks
• Pandas
• NumPy
• Matplotlib
• Anaconda
• Vscode
• We shall be using Google colab for this repo
• [Additional libraries as needed]

Installation

Install the required dependencies:

pip install -r requirements.txt

Project Structure

The repository is organized as follows:

G00dlife-datascience/
|-- notebooks/
|-- data/
|-- scripts/
|-- models/
|-- README.md
|-- requirements.txt

• Notebooks: All the notebooks in this repository are located here.
• Scripts: Project write ups and necessary documents here
• Introduction to Python Exercise:
• Solutions -Intro to Python:

Contributing

• Check Contributing.md for guidlines on how to contribute.
  
• If you find any issues or have suggestions, feel free to open an issue or submit a pull request.
  

Licence

• This repository is licenced under Apache-2.0 ,refer to the LICENCE.md for more details.

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