Topic: "handling-missing-values"
alejo1630/missing_values
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.
Language: Jupyter Notebook - Size: 1.81 MB - Last synced at: 7 days ago - Pushed at: about 1 month ago - Stars: 1 - Forks: 0
Ehsan-Behzadi/Online-Retail-Data-Analysis-and-Preprocessing
This project analyzes and preprocesses the Online Retail dataset to uncover insights into customer purchasing behaviors, sales trends, and product performance. It includes data cleaning, exploration, and visualization, with the goal of enhancing understanding of online retail dynamics.
Language: Jupyter Notebook - Size: 1.86 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0
Ehsan-Behzadi/Breast-Cancer-Prediction-Model
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.
Language: Jupyter Notebook - Size: 793 KB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 0 - Forks: 0
madhurimarawat/Data-Wrangling
This repository contains experiments on data wrangling techniques, focusing on methods for handling missing values, filtering, aggregation, and more.
Language: Jupyter Notebook - Size: 621 KB - Last synced at: 4 months ago - Pushed at: 5 months ago - Stars: 0 - Forks: 0
