Tag: machine learning

How many college football teams can you watch in-person in one football season?

The college football season once again came to an end back in January, which now leaves us college football fans with nothing to do but post football memes online and feign interest in other sports until August rolls around again.

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Machine Learning Madden NFL: The best player position switches for Madden 17

A couple weeks ago, I wrote about my initial efforts toward using machine learning to model the “master equations” that govern the Madden NFL player ratings system. This week, I’d like to put those models to use to compute the

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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.

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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

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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

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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

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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

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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?

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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

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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

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