This Notebook explores the impact of different missing data handling techniques on a medical dataset by analyzing missingness patterns, variable distributions, and inter-feature relationships to inform appropriate imputation strategies.

This repository contains experiments on data wrangling techniques, focusing on methods for handling missing values, filtering, aggregation, and more.

In this repository, you'll find all the code solutions I've completed during my TECHNOHACKS EDUTECH internship as a data analyst intern.

This project implements a machine learning model to predict breast cancer diagnosis. Utilizing techniques such as data preprocessing, feature selection, and various algorithms, the model aims to assist in early detection and improve healthcare outcomes. Explore the repository to understand the methodology and technologies used in this project.