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mattphotonman's Projects

bc icon bc

Template for Software Carpentry bootcamp site repository.

candle icon candle

Educational implementation of autograd similar to pytorch

cities_college_grads icon cities_college_grads

This is an attempt at trying to explain the observed distribution of college graduates in some American cities. Within the framework of the model, it is possible to tell whether there is a clustering effect, i.e. college grads tend to go to cities with other college grads, or whether the distribution is consistent with college grads moving to cities at random. This project is in response to the following article: http://www.nytimes.com/2012/05/31/us/as-college-graduates-cluster-some-cities-are-left-behind.html

jackknife icon jackknife

C++ classes that aid in doing jackknife resampling calculations. Some methods are general purpose, some are for specific projects of mine.

metropolis_example icon metropolis_example

Simple example of the Metropolis algorithm to create a single random variable with a normal distribution, mean 0 and standard deviation 1.

riddler_solutions icon riddler_solutions

Solutions to various problems from http://fivethirtyeight.com/tag/the-riddler/

shannon_entropy--python- icon shannon_entropy--python-

Tools for calculating the Shannon entropy of a text file. Here we are considering text files to be streams of letters, and look at sets of n consecutive letters. (We are not considering the text file to be a stream of English words.)

swc_yale_oct_2014 icon swc_yale_oct_2014

This is a repo to play around with for the SW carpentry bootcamp at Yale, October 2014.

tensorflow icon tensorflow

An Open Source Machine Learning Framework for Everyone

test_jackknife_method icon test_jackknife_method

Program for comparing jackknife estimates of the standard deviation of the mean of a quantity to the "actual" standard deviation. The "actual" standard deviation is calculate by repeating the experiment N times and calculating the standard deviation of the mean from these N samples.

yahtzee_widget--python- icon yahtzee_widget--python-

NOTE: CODE UNFINISHED. Code to find the optimal strategy for getting a certain combination (e.g. Yahtzee, four of a kind, full house) in a turn of Yahtzee, and to calculate the probability of getting it if you follow the optimal strategy. The desired combination is encoded by specifying point values for each possible roll of the dice at the end of the turn, and the code finds the strategy that maximizes the expectation value of the number of points. The expectation value of the number of points with the optimal strategy is also returned. If you want to know a probability of a certain combination, you can set the points for rolls belonging to that combination to 1, and set the points to 0 for all other rolls.

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