In this project I use classification models to predict potential donors given a set of demographic factors.
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Updated
Aug 8, 2017 - HTML
In this project I use classification models to predict potential donors given a set of demographic factors.
ML Project done in Udacity Course
Investigated factors affecting likelihood of donations being made using real census data. Developed naive classifier to compare testing results. Trained & tested several supervised machine learning models on preprocessed census data to predict donation likelihood. Selected best model based on accuracy, modified F-score metric, & algo efficiency.
Finding Charity Donors -- Udacity MLND
Udacity Machine Learning Engineer Nanodegree Supervised Learning Project: Finding Donors for CharityML
Machine Learning Engineer Nanodegree -Supervised Learning -Project: Finding Donors for CharityML
Apply supervised machine learning techniques and an analytical mind on data collected for the U.S. census to help CharityML (a fictitious charity organization) identify people most likely to donate to their cause
Finding Donor for CharityML - Machine Learning Nanodegree from Udacity
Applying Supervised learning techniques on data to help CharityML identify people most likely to donate to their cause.
Finding out the donors who earn more than $50K annually using Machine Learning
Machine Learning Engineer Nanodegree, Supervised Learning, Finding Donors for CharityML
Udacity Data Science Nanodegree program, supervised learning, finding donors project
Find Donors for CharityML for Udacity Machine Learning Engineer Nanodegree
Supervised Learning: Finding Donors for CharityML
My submission for udacity nanodegree finding-donors project
Build an algorithm to best identify potential donors of CharityML
Finding donors using supervised learning
Machine Learning Nano-degree Project : To help a charity organization identify people most likely to donate to their cause
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