KPNSTeam: Advancing Cancer Research through Machine Learning

Overview

Welcome to the KPNSTeam repository, a collaborative project focused on advancing cancer research using state-of-the-art machine learning techniques. This repository contains code, data, and documentation that support the development and validation of predictive models to improve cancer diagnosis, prognosis, and treatment.

Table of Contents

• Project Structure
• Research Objectives
• Getting Started
• Prerequisites
• Installation
• Usage
• Contributing
• License
• Contact

Project Structure

The repository is organized as follows:

Each directory and file is designed to facilitate the organization, execution, and analysis of the research process.

Research Objectives

The main objectives of this project are:

• Data Preprocessing: Cleaning and preparing raw data for analysis.
• Exploratory Data Analysis: Understanding the data through visualization and statistical analysis.
• Model Training: Developing machine learning models to predict cancer outcomes.
• Model Evaluation: Assessing the performance of the models using various metrics.
• Result Visualization: Creating visual representations of the model performance and findings.

Getting Started

Follow these steps to get started with the KPNSTeam repository.

Prerequisites

Ensure you have the following software and packages installed:

• Python version 3.8 or later
• Jupyter Notebook
• Pandas
• NumPy
• scikit-learn
• Matplotlib
• Seaborn

Installation

Clone the repository to your local machine using the following command:

git clone https://github.com/Krishiv111/KPNSTeam.git