Finding doners for charityML

Build an algorithm to best identify potential donors of CharityML

We developed a model that will predict the likelihood that a given employed citizens of CA as a potential donor of a fictitious charity organization, Charity ML.

Finding Donor for CharityML - Machine Learning Nanodegree from Udacity

Finding Donors for CharityML using supervised learners.

Applying Supervised learning techniques on data to help CharityML identify people most likely to donate to their cause.

CharityML is a fictitious charity organization that was established to provide financial support for people eager to learn machine learning.

Employing several supervised algorithms to accurately model individuals' income.

Applying Supervised learning techniques on data to help CharityML identify people most likely to donate to their cause.

Machine Learning Engineer Nanodegree, Supervised Learning, Finding Donors for CharityML

Supervised Learning - Finding Donors for CharityML

Udacity Machine Learning Nanodegree Supervised Learning Project

Applied supervised learning techniques on data collected for the U.S. census to help CharityML (a fictitious charity organization) identify people most likely to donate to their cause.

This project help identify people who are most likely to donate to CharityML(fictious charity organization)

Finding donors using supervised learning

Project-1 of Udacity's Introduction to Machine Learning with TensorFlow Nanodegree. "Finding Donors for CharityML" is a Supervised Learning Project with Scikit-learn that aims to build a model that accurately predicts whether an individual earns more than $50,000