I build things with statistics, code, and prose.
Photo by ginnerobot
Statistical principles for decision making
How to measure whether your marketing is profitable
Noticing unexpected observations among an ocean of expected ones.
Featured on DataScienceCentral.com and @analyticbridge.
Predicting if customers plan to leave and finding the best intervention
How probability distributions are related
It’s how they say spending and income.
Received the “Deep Thought Badge” and Honorable Mention in Google & Eyebeam’s Data Visualization Challenge.
A predictive model that uses the title, topic, and publish date of TED talks to estimate the number of times they will be viewed.
A program that evolves a prediction model for a given data set.
A website that ranks links based on votes. It aims to learn the most from each vote by selecting which articles visitors vote on and using a Bayesian estimator.
Interesting hack for following a topic HN-style […]Hilary Mason (@hmason), Data Scientist in Residence at Accel
I presently work as a Data Science Lead on a remote team.
I have a masters in Applied Statistics and have been excitedly coding for over a decade. My specialties include Time Series Analysis, Bayesian Probabilistic Programming, and NLP.
Feel free to connect on LinkedIn