jeh0753

boomsetdataclean

Tool for cleaning event attendance data from Boomset

churn_case

Identified customers who are likely to churn using logistic regression and Random Forest classifiers. Evaluated results using Area Under the Curve (AUC) score.

coinyasa

dotfiles

drafttest

kmeans

K Means algorithm coded in Scipy and Numpy, tested on Iris dataset.

kruegerreplication

A Replication of Alan Krueger’s "What Makes a Terrorist?"

MNIST

C-NN using Keras and Theano to categorize handwritten numbers, 99.3% accuracy

sparseMF

Open source matrix factorization recommender for sparse matrices

tractor_case

Predicted tractor sales prices at auctions using multiple datasets. Applied linear regression, imputing missing data with k-Nearest Neighbors (kNN), and evaluated results using root mean squared logarithmic error (RMSLE score).

jeh0753/sparseMF

Open source matrix factorization recommender for sparse matrices

jeh0753/tractor_case

Predicted tractor sales prices at auctions using multiple datasets. Applied linear regression, imputing missing data with k-Nearest Neighbors (kNN), and evaluated results using root mean squared logarithmic error (RMSLE score).

jeh0753/boomsetdataclean

Tool for cleaning event attendance data from Boomset

jeh0753/churn_case

Identified customers who are likely to churn using logistic regression and Random Forest classifiers. Evaluated results using Area Under the Curve (AUC) score.

jeh0753/coinyasa

jeh0753/dotfiles

jeh0753/drafttest

jeh0753/kmeans

K Means algorithm coded in Scipy and Numpy, tested on Iris dataset.

jeh0753/kruegerreplication

A Replication of Alan Krueger’s "What Makes a Terrorist?"

jeh0753/MNIST

C-NN using Keras and Theano to categorize handwritten numbers, 99.3% accuracy

jeh0753/fancyimpute

Multivariate imputation and matrix completion algorithms implemented in Python

jeh0753/first_app

first app for ruby rails tutorial

jeh0753/fraud_detection

A Gradient Boosted Model that triages fraudulent events, and recommends whether or not to flag a given event for further investigation.

jeh0753/hello-world

jeh0753/jeh0753.github.io

jeh0753/knn

K Nearest Neighbors algorithms coded in numpy and scipy. Includes both a matrix imputer and a supervised learning KNN algorithm.

jeh0753/MineSweeperNeuralNet

Teaching a neural net to play mine sweeper

jeh0753/models

Models and examples built with TensorFlow

jeh0753/newgittest

jeh0753/night_sky

Unsupervised Learning case study on UFO sighting data.

jeh0753/NN_fun

Some simple examples showing off power of Neural Networks

jeh0753/scala_practice

Simple solutions to scala challenges

jeh0753/scikit-learn

scikit-learn: machine learning in Python

jeh0753/T-Watch

Real Time Twitter Sentiment Analysis Product

jeh0753/timetofailure

Kaggle competition and Linear Algebra practice