July 2017

How to use H2O with R on HDInsight

July 31, 2017 | David Smith

H2O.ai is an open-source AI platform that provides a number of machine-learning algorithms that run on the Spark distributed computing framework. Azure HDInsight is Microsoft's fully-managed Apache Hadoop platform in the cloud, which makes it easy to spin up and manage Azure clusters of any size. It's also ... [Read more...]

Machine Learning Explained: Dimensionality Reduction

July 31, 2017 | EnhanceDataScience

Dealing with a lot of dimensions can be painful for machine learning algorithms. High dimensionality will increase the computational complexity, increase the risk of overfitting (as your algorithm has more degrees of freedom) and the sparsity of the data will grow. Hence, dimensionality reduction will project the data in a ...
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Google Vision API in R – RoogleVision

July 31, 2017 | Scott Stoltzman

Using the Google Vision API in R Utilizing RoogleVision After doing my post last month on OpenCV and face detection, I started looking into other algorithms used for pattern detection in images. As it turns out, Google has done a phenomenal job with their Vision API. It’s absolutely incredible ...
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Matching, Optimal Transport and Statistical Tests

July 30, 2017 | arthur charpentier

To explain the “optimal transport” problem, we usually start with Gaspard Monge’s “Mémoire sur la théorie des déblais et des remblais“, where the the problem of transporting a given distribution of matter (a pile of sand for instance) into another (an excavation for instance). This problem ...
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Scripting for data analysis (with R)

July 30, 2017 | mrtnj

Course materials (GitHub) This was a PhD course given in the spring of 2017 at Linköping University. The course was organised by the graduate school Forum scientium and was aimed at people who might be interested in using R for data analysis. The materials developed from a part of a ... [Read more...]

Understanding Overhead Issues in Parallel Computation

July 29, 2017 | matloff

In my talk at useR! earlier this month, I emphasized the fact that a major impediment to obtaining good speed from parallelizing an algorithm is systems overhead of various kinds, including: Contention for memory/network. Bandwidth limits — CPU/memory, CPU/network, CPU/GPU. Cache coherency problems. Contention for I/O ... [Read more...]

Forecasting workshop in Perth

July 29, 2017 | R on Rob J Hyndman

On 26-28 September 2017, I will be running my 3-day workshop in Perth on “Forecasting: principles and practice” based on my book of the same name. Topics to be covered include seasonality and trends, exponential smoothing, ARIMA modelling, dynamic regression and state space models, as well as forecast accuracy methods and ... [Read more...]

More documentation for Win-Vector R packages

July 29, 2017 | John Mount

The Win-Vector public R packages now all have new pkgdown documentation sites! (And, a thank-you to Hadley Wickham for developing the pkgdown tool.) Please check them out (hint: vtreat is our favorite). The package sites: cdata replyr seplyr sigr vtre...
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R Markdown exercises part 1

July 29, 2017 | Euthymios Kasvikis

INTRODUCTION R Markdown is one of the most popular data science tools and is used to save and execute code, create exceptional reports whice are easily shareable. The documents that R Markdown provides are fully reproducible and support a wide variety of static and dynamic output formats. Using markdown syntax, ... [Read more...]

Stan Weekly Roundup, 28 July 2017

July 28, 2017 | Bob Carpenter

Here’s the roundup for this past week. Michael Betancourt added case studies for methodology in both Python and R, based on the work he did getting the ML meetup together: RStan workflow PyStan workflow Michael Betancourt, along with Mitzi Morris, Sean Talts, and Jonah Gabry taught the women in ... [Read more...]

Stan Weekly Roundup, 28 July 2017

July 28, 2017 | Bob Carpenter

Here’s the roundup for this past week. Michael Betancourt added case studies for methodology in both Python and R, based on the work he did getting the ML meetup together: RStan workflow PyStan workflow Michael Betancourt, along with Mitzi Morris, Sean Talts, and Jonah Gabry taught the women in ... [Read more...]
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