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John Ramey · Statistics and Machine Learning

The personal site of John Ramey. To discuss statistics, machine learning, and other endeavors. Statistics and Machine Learning. Configuring IPython Notebook Support for PySpark. Is a great way for performing large-scale data processing. Lately, I have begun working with PySpark. A way of interfacing with Spark through Python. After a discussion with a coworker, we were curious whether PySpark could run from within an IPython Notebook. Installing Python Data Science Stack on Yosemite. Given that I had bar...

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John Ramey · Statistics and Machine Learning | ramhiser.com Reviews

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The personal site of John Ramey. To discuss statistics, machine learning, and other endeavors. Statistics and Machine Learning. Configuring IPython Notebook Support for PySpark. Is a great way for performing large-scale data processing. Lately, I have begun working with PySpark. A way of interfacing with Spark through Python. After a discussion with a coworker, we were curious whether PySpark could run from within an IPython Notebook. Installing Python Data Science Stack on Yosemite. Given that I had bar...

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John Ramey · Statistics and Machine Learning | ramhiser.com Reviews

https://ramhiser.com

The personal site of John Ramey. To discuss statistics, machine learning, and other endeavors. Statistics and Machine Learning. Configuring IPython Notebook Support for PySpark. Is a great way for performing large-scale data processing. Lately, I have begun working with PySpark. A way of interfacing with Spark through Python. After a discussion with a coworker, we were curious whether PySpark could run from within an IPython Notebook. Installing Python Data Science Stack on Yosemite. Given that I had bar...

INTERNAL PAGES

ramhiser.com

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A Brief Look at Mixture Discriminant Analysis · John Ramey

http://ramhiser.com/2013/07/02/a-brief-look-at-mixture-discriminant-analysis

The personal site of John Ramey. To discuss statistics, machine learning, and other endeavors. Statistics and Machine Learning. A Brief Look at Mixture Discriminant Analysis. Lately, I have been working with finite mixture models for my postdoctoral work on data-driven automated gating. As far as I am aware, there are two main approaches (there are lots and lots of variants! To applying finite mixture models to classfication:. The Fraley and Raftery approach. Via the mclust R package. To see how well the...

2

About Me · John Ramey

http://ramhiser.com/about.html

The personal site of John Ramey. To discuss statistics, machine learning, and other endeavors. Statistics and Machine Learning. Lead Data Scientist at uStudio. Enamored with machine learning. Write lots of Python and R code. Passionate about exercise and nutrition. Fan Sic ‘em, Bears! Soccer referee for over 20 years.

3

Installing Python Data Science Stack on Yosemite · John Ramey

http://ramhiser.com/2015/01/24/installing-python-data-science-stack-on-yosemite

The personal site of John Ramey. To discuss statistics, machine learning, and other endeavors. Statistics and Machine Learning. Installing Python Data Science Stack on Yosemite. I was attempting to install the Python data-science stack within a fresh virtual environment on my Mac with OS X 10.10.1 (Yosemite) but encountered various frustrating errors. I logged my steps below that eventually yielded a successful installation. My primary goal was actually to install version 0.15.2 of scikit-learn. In file ...

4

Configuring IPython Notebook Support for PySpark · John Ramey

http://ramhiser.com/2015/02/01/configuring-ipython-notebook-support-for-pyspark

The personal site of John Ramey. To discuss statistics, machine learning, and other endeavors. Statistics and Machine Learning. Configuring IPython Notebook Support for PySpark. Is a great way for performing large-scale data processing. Lately, I have begun working with PySpark. A way of interfacing with Spark through Python. After a discussion with a coworker, we were curious whether PySpark could run from within an IPython Notebook. Create PySpark profile for IPython. Simple word count example. Set thi...

5

MLB Rankings Using the Bradley-Terry Model · John Ramey

http://ramhiser.com/2013/08/31/mlb-rankings-using-the-bradley-terry-model

The personal site of John Ramey. To discuss statistics, machine learning, and other endeavors. Statistics and Machine Learning. MLB Rankings Using the Bradley-Terry Model. Before we discuss the rankings, we need some data. Let’s scrape ESPN’s MLB Standings Grid. For a win-loss matchups of any two MLB teams for the current season. Perhaps to simplify the tables and to reduce the sparsity resulting from interleague play. Scraping ESPN with a Python Script. Here’s the Python code. Feel free to fork it.

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bayesiancomputation.wordpress.com

The Likelihood That Wouldn’t Die | Adventures in Bayesian Computation

https://bayesiancomputation.wordpress.com/2010/06/26/the-likelihood-that-wouldnt-die

Adventures in Bayesian Computation. Markov chains, priors, and DAGs, oh my! Laquo; Building JAGS from source on Mac OS X. Debugging JAGS on Mac OS X. The Likelihood That Wouldn’t Die. A question recently arose on the BUGS mailing list that is worth discussing in some detail, because it illustrates a nonobvious case requiring some thought about the prior. The Fader-Hardie customer retention model. May be described as follows. Customers purchase a contract and may let it expire at the end of each year.

higherorderlogic.com

Bad code isn't Technical Debt, it's an unhedged Call Option – Stephen Freeman

http://higherorderlogic.com/2010/07/bad-code-isnt-technical-debt-its-an-unhedged-call-option

Skip to Content ↓. Bad code isn't Technical Debt, it's an unhedged Call Option. Jul 23rd, 2010. I’d been meaning to write this up for a while, and now Nat Pryce has written up the 140 character version. This is all Chris Matts. I “write” a Call Option. I can take a chance and just collect the premium. This is called an unhedged, or “Naked”. Call In the financial world this is risky because it has unlimited downside, I have to supply the santas. They cost me to provide. Call options are a better model tha...

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John Ramey · Statistics and Machine Learning

The personal site of John Ramey. To discuss statistics, machine learning, and other endeavors. Statistics and Machine Learning. Configuring IPython Notebook Support for PySpark. Is a great way for performing large-scale data processing. Lately, I have begun working with PySpark. A way of interfacing with Spark through Python. After a discussion with a coworker, we were curious whether PySpark could run from within an IPython Notebook. Installing Python Data Science Stack on Yosemite. Given that I had bar...

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