Machine Learning Project

Welcome to the Machine Learning Project! This repository contains all the resources, code, and data used in our project, along with links to the project website and data files.

This repository contains all the assignments and projects for the Generative AI subject.

Project Overview

This project focuses on exploring and applying various machine learning techniques to solve real-world problems. The project includes:

• Development of machine learning models
• Data preprocessing and visualization
• Performance evaluation and analysis

Project Website

Explore our project and its findings on our official website: Project Website

Data Files

Access the datasets used in this project via the link below: Data Files

Team Members

This project was collaboratively developed by the following team members:

1. Amit
2. Niveditha
3. Atharva
4. Shubham

Repository Structure

• Code.ipynb: Contains the Jupyter Notebook used for code implementation.
• Data: Includes all the datasets used in the project (accessible via the provided data files link).
• Documentation: Additional resources and detailed explanations of the methodologies.

📌 Note

If the .ipynb files are not rendering correctly on GitHub, you can view them using nbviewer:

1. Go to nbviewer.
2. Paste the URL of the .ipynb file in the input box.
3. Click "Go" to view the notebook.

How to Use

1. Visit the Project Website for a detailed overview of our work.
2. Download the required data from the Data Files link.
3. Open the Code.ipynb file to review and run the machine learning code.

Acknowledgments

We would like to thank our mentors, peers, and all who supported us throughout this project.

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For any questions or contributions, feel free to reach out to any of the team members.