MungeX-3D

Data, Dogs, Ducati (and Baseball)


How to invert a matrix in r

#Creating a Hand Rolled Inverse Matrix in *R* #Lesson One ###Build the matrix (note: this example is a symmetrical matrix); the transpose of A is equal to A
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Iris Apocalypse Now: Fisher's Data Rescaled

8 May 2018 – The Machine Learning Repository at the Univerity of California, Irvine, states R.A. Fisher’s iris data set, first published in 1936, “is perhaps the best known database to be found in the pattern recognition literature.” I don’t think there is any user of R or Python who is not familiar with its 150 observations of three types of iris –- setosa, versicolor, and virginica.

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Frankencode: Using Python's Seaborn Creature in R

2 May 2018 – The integration of Python and R has been going on for a while and the benefits tend to increase. Earlier, we took a look at loading Python’s keras package into R. We found the exercise to be worthwhile and the results impressive, but there were some quirks that generally aren’t mentioned in the official documentation. Using Python’s signature libraries – seaborn, matplotlib, and pandas – provide similar benefits and challenges.

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purrrs Like a Kitten 'til the Lake Pipes RoaR

28 April 2018 – I really should make minimal effort to resist an opportunity to open a data analysis blog post with Beach Boys’ lyrics, but this time the temptation is overwhelming. We use the purrr package to show how to let your pipes roar in R.

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Coming to $terms in R

15 April 2018 – A recent analysis I worked on involved building a log regression and some ensemble methods using a data set with about 25 features, in addition to the target. It was an analysis of customer churn in the telecom industry. If you are interested, you can find the problem statement here, the annotated code here, and the raw code in my GitHub repository.

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Building a Pivot Table in R (with a Bit of SQL)

9 April 2018 – Building an Excel-style pivot table in R is not a problem. We are going to cover the process in this post. Like most data problems, the most involved part is cleaning and structuring the data in a manner suitable for the task. Those steps are decribed below, as well.

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Loading Keras into R, Part 2

15 March 2018 – So I learned in the previous post that if an R user wants to load the Python keras library into R to run neural net models, it is necessary to load Python first. The keras package in R is an interface with Python, not a standalone package.

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Loading Keras into R, Part 1

14 March 2018 – Late last year, Matt Dancho had a post on deep learning celebrating the arrival of the Python keras package for R. It is a very good tutorial on using artificial neural networks (ANN) to solve complicated business problems, well worth checking out.

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