Welcome to the Data Science Playground! 🦾

This repository serves as a showcase of various data science projects, exploratory and statistical data analysis, data visualizations, machine learning model development, optimization, and evaluation.

Table of Contents 📋

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• Introduction
• Folder Structure
• Usage

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Introduction 🤖

In this repository, you'll find a collection of Jupyter notebooks, some containing SQL and Python code for a range of data science projects. These projects cover a wide array of topics and techniques within the field of data science.

Folder Structure 🗃️

The repository is organized as follows:

DataSciencePlayground
|--- Project Name 1
|    |--- assets			# Additional files used in Project Name 1
|    |--- datasets			# Dataset(s) used in Project Name 1
|    |--- notebook			# Jupyter notebook for Project Name 1
|    |--- presentation			# Jupyter presentation for Project Name 1
|    `--- README.md			# Detailed README for Project Name 1
|--- Project Name 2
|    |--- assets			# Additional files used in Project Name 2
|    |--- datasets			# Dataset(s) used in Project Name 2
|    |--- notebook			# Jupyter notebook for Project Name 2
|    |--- presentation			# Jupyter presentation for Project Name 2
|    `--- README.md			# Detailed README for Project Name 2
|--- ...
`--- README.md				# Main repository README (this file)

📝 The contents of the individual subdirectories vary depending on the projects' requirements.

Usage 🚀

To interact with the individual projects:

1. Navigate to the project folder of interest.
2. Open the Jupyter notebook associated with the project.
3. Follow the instructions within the notebook to reproduce the analysis or run the code.