FDS_Final_Project

Introduction

Welcome to the FDS_Final_Project repository! This project is a comprehensive analysis and exploration in the field of Binary Classification.

Contents

• Presentations:
  • Final_Presentation_2_Chatterjee_Ghosh_Jezequel_Atayev.pdf: Our final presentation detailing the key findings and insights.
  • First_Presentation_2_Chatterjee_Ghosh_Jezequel_Atayev.pdf: The initial presentation outlining the project's scope and initial hypotheses.
• Jupyter Notebook:
  • Notebook_Chatterjee_Ghosh_Jèzèquel_Atayev.ipynb: Contains all the code, analyses, and visualizations that drive this project. Here, you'll find a detailed exploration of data, application of various algorithms, and our analytical methodologies.
• Report:
  • Report_Chatterjee_Ghosh_Jèzèquel_Atayev_Report.pdf: A comprehensive report discussing the project's methodology, results, and conclusions.
• Datasets:
  • train.csv: The training dataset used for model building.
  • test.csv: The test dataset used for model evaluation.
  • sample_submission.csv: An example of submission format for predictive modeling.

Installation and Usage

To use the Jupyter notebook:

1. Ensure you have Jupyter Notebook installed. If not, install it using pip install notebook.
2. Clone this repository to your local machine.
3. Navigate to the notebook directory and launch Jupyter Notebook.
4. Open Notebook_Chatterjee_Ghosh_Jèzèquel_Atayev.ipynb and run the cells to see the analysis in action.