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.
- Project Structure
- Research Objectives
- Getting Started
- Prerequisites
- Installation
- Usage
- Contributing
- License
- Contact
The repository is organized as follows:
Each directory and file is designed to facilitate the organization, execution, and analysis of the research process.
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.
Follow these steps to get started with the KPNSTeam repository.
Ensure you have the following software and packages installed:
- Python version 3.8 or later
- Jupyter Notebook
- Pandas
- NumPy
- scikit-learn
- Matplotlib
- Seaborn
Clone the repository to your local machine using the following command:
git clone https://github.com/Krishiv111/KPNSTeam.git