This repository contains my projects and tasks completed during the Graduate Rotational Internship Program (GRIP) by The Sparks Foundation. These projects showcase my work and contributions throughout the internship.

• Introduction
• Projects
• Directory Structure
• License
• Contact

Welcome to my GRIP repository, where I have documented my progress and achievements during the internship. This README provides an overview of the projects and tasks I've completed.

Here's a brief description of the projects included in this repository:

• Description: This project involves predicting student scores based on their study hours. It's a data analysis and machine learning project aimed at understanding the relationship between study time and academic performance.

• Description: This project involves the analysis of the Iris dataset to determine the optimal number of clusters for K-Means clustering. The results are visually represented to showcase the data's natural groupings. The project demonstrates essential techniques in data exploration, clustering, and visualization, making it a valuable learning resource for data science enthusiasts.

The repository has the following structure:

• Project 01: The main directory for Project 01.

  • Data: Contains datasets in .csv format used in the project.
  • Notebook: Includes Jupyter notebooks related to the project.

• Project 02: The main directory for Project 02.

  • Notebook: The Jupyter Notebook for Project 02.

You can explore each subdirectory to find specific project resources and files.

This project is licensed under the terms of the [License Name] License. You can find detailed licensing information in the LICENSE file.

If you have any questions or would like to get in touch with me, you can reach out via:

• Email
• LinkedIn