rutuja-gadhave

Advavanced-Java-programs

All programs of advanced java

Calculator

Calculator application developed in advanced Java.

Data-Science-Classification-project-Finding-donors-for-charity

This is data science project finds individuals having income greater than 50K for charity donation

GRIP-TSF-tasks

Java-programs

All core Java Programs

Language-converter-Application

MuleSoft

Organization-jobs-and-data-Management-System

This is simple Java Swing desktop application for managing organisation's jobs and employees data.

rutuja-gadhave.github.io

My portfolio website.

Travels-and-Tourism-wesite

This is simple travels and tourism website which gives information about tourism and we can book our tour.

rutuja-gadhave/Language-converter-Application

rutuja-gadhave/Travels-and-Tourism-wesite

This is simple travels and tourism website which gives information about tourism and we can book our tour.

rutuja-gadhave/Advavanced-Java-programs

All programs of advanced java

rutuja-gadhave/Calculator

Calculator application developed in advanced Java.

rutuja-gadhave/Data-Science-Classification-project-Finding-donors-for-charity

This is data science project finds individuals having income greater than 50K for charity donation

rutuja-gadhave/GRIP-TSF-tasks

rutuja-gadhave/Java-programs

All core Java Programs

rutuja-gadhave/MuleSoft

rutuja-gadhave/Organization-jobs-and-data-Management-System

This is simple Java Swing desktop application for managing organisation's jobs and employees data.

rutuja-gadhave/rutuja-gadhave.github.io

My portfolio website.

rutuja-gadhave/Sqlite-Java-database-operations

rutuja-gadhave/Telecom-Customer-Churn-Prediction-and-Analysis

Customer churn is a major problem and one of the most important concerns for large companies. Due to the direct effect on the revenues of the companies, especially in the telecom field, companies are seeking to develop means to predict potential customer to churn. Therefore, finding factors that increase customer churn is important to take necessary actions to reduce this churn. The main contribution of our work is to develop a churn prediction model which assists telecom operators to predict customers who are most likely subject to churn. In this project we will able to predict the churn value of customers based on the packages they select, their gender and other information. For stable and accurate prediction Logistic Regression Machine Learning algorithm will be used. This project was build to estimate churners for companies in the telecommunication industry