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Machine Learning Madden NFL: How Madden player ratings are actually calculated

For the past few months, I’ve been playing Madden NFL 17 in my free time. I really enjoy the team-building aspect of the franchise mode, where I’ve taken on challenges such as finally bringing the Lombardi trophy home to Philadelphia.

Posted in machine learning Tagged with: , , ,

Evolution of active categorical image classification via saccadic eye movement

I put together a couple demo videos for our Active Categorical Classifier (ACC) project that we’ll be presenting at the PPSN 2016 conference. If you’re interested in this project and can’t wait for PPSN, we have: a preprint of the

Posted in machine learning, research Tagged with: , ,

The Optimal U.S. National Parks Centennial Road Trip

In August 2016, the National Park Service celebrates their 100th year of managing the United States’ system of beautiful national parks. So what’s a better way to celebrate 100 years of stewardship than to visit all of the national parks

Posted in data visualization, machine learning Tagged with: , , , ,

Computing optimal road trips on a limited budget

About a year ago, I wrote an article introducing the concept of optimizing road trips using a combination of genetic algorithms and Google Maps. During that time, I’ve given some thought to how I could make that algorithm more useful

Posted in data visualization, machine learning, python Tagged with: , , , , ,

TPOT: A Python tool for automating data science

Machine learning is often touted as: A field of study that gives computers the ability to learn without being explicitly programmed. Despite this common claim, anyone who has worked in the field knows that designing effective machine learning systems is

Posted in machine learning, python, research Tagged with: , ,

Introducing TPOT, the Data Science Assistant

Some of you might have been wondering what the heck I’ve been up to for the past few months. I haven’t been posting much on my blog lately, and I haven’t been working on important problems like solving Where’s Waldo?

Posted in machine learning, python, research Tagged with: , , , , ,

Analyzing the health of Philadelphia’s bike share system

Last month, I wrote about my initial attempts to model and predict the usage patterns of Indego, Philadelphia’s new bike share system. To recap: If you’ve ever used a bike share before, you know that one of the biggest fears

Posted in analysis, data visualization Tagged with: , , , ,

Visualizing Indego bike share usage patterns in Philadelphia

One of the many things that I love about my new home town of Philadelphia is that the government openly shares curated data sets covering most of the governmental functions. Since I recently joined Philadelphia’s Indego bike share program, I

Posted in analysis, data visualization Tagged with: , , , ,

Optimized walking tours of New York City and Philadelphia

In the past couple weeks, I’ve shown you how to use machine learning to improve the efficiency of road trips all over the world, including the U.S., Europe, and South America. In this post, I’d like to show you how

Posted in analysis, data visualization, machine learning Tagged with: , , , ,

Pure Michigan road trip, optimized

For the past couple weeks, I’ve been computing optimal road trips across the U.S. and Europe. This time, as a shout-out to my current home state, I made a road trip around Michigan. With the snow melting and a warm

Posted in analysis, data visualization, machine learning Tagged with: , , , ,

About this blog

This blog is my labor of love, and I've spent hundreds of hours working on the projects that you'll read about here. Generally, I write about data visualization and machine learning, and sometimes explore out-of-the-box projects at the intersection of the two. I hope you enjoy my projects as much as I have.

If you would like to use one of my graphs on your website or in a publication, please feel free to do so with appropriate attribution, but I would appreciate it if you email me first to let me know.

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