Monthly Archives: June 2013

My Talk at Boston Python

June 25, 2013
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I just gave a talk at Boston Python about natural language processing in general, and edX ease and discern in specific. You can find the presentation source here, and the web version of it here. There is a video of it here. Nelle Varoquaux and Micha...

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My talk at Boston Python

June 25, 2013
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I just gave a talk at Boston Python about natural language processing in general, and edX ease and discern in specific. You can find the presentation source here, and the web version of it here. There is a video of it here. Nelle Varoquaux and Micha...

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rClr: low level access to .NET from R

June 25, 2013
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rClr: low level access to .NET from R

rClr is a package to access arbitrary .NET code seamlessly. The "CLR" acronym part of the package name stands for Common Language Runtime. C# and R being languages I regularly use, I have felt the need for better interoperability between these for a fe...

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Split violin plots

June 25, 2013
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Split violin plots

(This article was first published on Ecology in silico, and kindly contributed to R-bloggers) Violin plots are useful for comparing distributions. When data are grouped by a factor with two levels (e.g. males and females), you can split the violins in half to see the difference between groups. Consider a 2 x 2 factorial experiment: treatments A and B...

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Sample size calculations equivalent to Stata functions

June 25, 2013
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A comprehensive guide to time series plotting in R

June 25, 2013
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A comprehensive guide to time series plotting in R

As R has evolved over the past 20 years its capabilities have improved in every area. The visual display of time series is no exception: as the folks from Timely Portfolio note that: Through both quiet iteration and significant revolutions, the volunteers of R have made analyzing and charting time series pleasant. R began with the basics, a simple...

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Natural Language Processing Tutorial

June 25, 2013
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Natural Language Processing Tutorial

Introduction This will serve as an introduction to natural language processing. I adapted it from slides for a recent talk at Boston Python. We will go from tokenization to feature extraction to creating a model using a machine learning algorithm. The goal is to provide a reasonable baseline on top of which more complex natural language processing can be done, and...

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My Talk at Boston Python

June 25, 2013
By

I just gave a talk at Boston Python about natural language processing in general, and edX ease and discern in specific. You can find the presentation source here, and the web version of it here. There is a video of it here. Nelle Varoquaux and Michael ...

Read more »

Getting started with R

June 25, 2013
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Getting started with R

I wanted to avoid advanced topics in this post and focus on some “blocking and tackling” with R in an effort to get novices started.  This is some of the basic code I found useful when I began using R just over 6 weeks ago. Reading in data from a .csv file is a breeze with this command. > data =...

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The Dream 8 Challenges

June 25, 2013
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The Dream 8 Challenges

The 8th iteration of the DREAM Challenges are underway. DREAM is something like the Kaggle of computational biology with an open science bent. Participating teams apply machine learning and statistical modeling methods to biological problems, competing to achieve the best predictive accuracy. This year's three challenges focus on reverse engineering cancer, toxicology and the kinetics of...

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