exploratory data analysis

Dies ist eine einfache Datenanalyse, die auf dem Titanic-Datensatz durchgeführt wurde.

This project predicts house prices using machine learning models based on the King County House Sales dataset. It explores Simple Linear, Multiple Linear, Polynomial, and Ridge Regression models, comparing their performance in terms of accuracy. The best model identified is Polynomial Regression, achieving an R² score of 0.75.

An application for immediate treatment in emergency situations via centrally managed health camps.

Titanic veri seti üzerinde yapmış olduğumuz basit bir veri analizidir.

Titanic veri seti üzerinde yapmış olduğumuz basit bir veri analizidir.

Machine Learning - Recommendation System

Machine Learning - Binary Classification

Machine Learning - Multiclass Classification

Machine Learning - Classification Problem

Machine Learning - Binary Classification

Exploratory Data Analysis (EDA) on Haberman Dataset. Feature Importance.

Cette analyse a pour but d’explorer le comportement historique de ventes de livres dans la région de Montréal et dans la région de Québec entre les années 2010 et 2019.

Data mining & prediction of admission from different grades and parameters. Dataset created for prediction of Graduate Admissions from an Indian perspective.

Using machine learning methodology to create a model that predicts which passengers survived the Titanic shipwreck under data science analysis flow from explore data analysis to model selection.

Using the fund data from the web scraping to established the model to predict the net asset value of the fund from the data clean, data pre-processing, model established and model selection.

Established the binary classification system to predict the client required if the bank product order; for bank marketing, this topic focus on the minority of the people who order the product.

Materials from guest lecture on using maps in exploratory data analysis for Vanderbilt Data Science program.