2018

Deep learning in Satellite imagery

December 4, 2018 | Damian Rodziewicz

In this article, I hope to inspire you to start exploring satellite imagery datasets. Recently, this technology has gained huge momentum, and we are finding that new possibilities arise when we use satellite image analysis. Satellite data changes the game because it allows us to gather new information that is ...
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Starspace for NLP #nlproc

December 4, 2018 | Super User

Our recent addition to the NLP R universe is called R package ruimtehol which is open sourced at https://github.com/bnosac/ruimtehol This R package is a wrapper around Starspace which provides a neural embedding model for doing the following on text: Text classification Learning word, sentence or document ... [Read more...]

Day 04 – little helper evenstrings

December 4, 2018 | Jakob Gepp

We at STATWORX work a lot with R and we often use the same little helper functions within our projects. These functions ease our daily work life by reducing repetitive code parts or by creating overviews of our projects. At first, there was no plan to make a package, but ...
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An Introduction to H2O Using R

December 3, 2018 | R on orrymr.com

1. Introduction In this post we discuss the H2O machine learning platform. We talk about what H2O is, and how to get started with it, using R - we create a Random Forest which we use to classify the Iris Dataset. 2. What is H2O? The definition foun... [Read more...]

My 2018 #rstats year in review

December 3, 2018 | Matt's R Blog

This past year in R has been a good one for me; productive, exciting, different. I decided it was worth taking a moment to reflect and share. Goals were set and met. There were also unexpected changes. CRAN A year ago, at the tail end of 2017, I pu...
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Very Non-Standard Calling in R

December 3, 2018 | John Mount

Our group has done a lot of work with non-standard calling conventions in R. Our tools work hard to eliminate non-standard calling (as is the purpose of wrapr::let()), or at least make it cleaner and more controllable (as is done in the wrapr dot pipe). And even so, we ... [Read more...]

AzureVM: managing virtual machines in Azure

December 3, 2018 | Hong Ooi

This is the next article in my series on AzureR, a family of packages for working with Azure in R. I’ll give a short introduction on how to use AzureVM to manage Azure virtual machines, and in particular Data Science Virtual Machines (DSVMs). Creating a VM Creating a VM ... [Read more...]

Day 03 – little helper multiplot

December 3, 2018 | Jakob Gepp

We at STATWORX work a lot with R and we often use the same little helper functions within our projects. These functions ease our daily work life by reducing repetitive code parts or by creating overviews of our projects. At first, there was no plan to make a package, but ...
[Read more...]

An Utility Function For Monotonic Binning

December 2, 2018 | statcompute

In all monotonic algorithms that I posted before, I heavily relied on the smbinning::smbinning.custom() function contributed by Herman Jopia as the utility function generating the binning output and therefore feel deeply indebted to his excellent work. However, the availability of smbinning::smbinning.custom() function shouldn’t become my ... [Read more...]

A few thoughts on R packages

December 2, 2018 | R-bloggers on inSileco

Jonas Geschke, Ignasi Bartomeus and I have recently released rcites v-1.0.0 on CRAN, a R client for the Species+ API after it has been reviewed by rOpenSci. In this post, I would like to share this recent experience as well as several valuable resources. What is an R package? In ...
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Introduction to chartbookR

December 2, 2018 | Posts on Applied Economic R-esearch

“Data scientists … spend from 50 percent to 80 percent of their time … collecting and preparing unruly digital data, before it can be explored for useful nuggets.” (— New York Times). The chartbookR package allows the convenient creation of economic and financial data chartbooks. It handles most of the data wrangling and can thus ...
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Linear Classification Models – Hepatic Dataset

December 2, 2018 | Posts on Anything Data

This post is following exercise 1 in Chapter 12 of Applied Predicative Modeling. Here I use the machine learning package CARET in R to make classification models; in particular, the linear classification models discussed in Chapter 12. The dataset in question is about hepatic injury (liver damage). It includes a dataframe of biological ... [Read more...]

Introduction to chartbookR

December 2, 2018 | Posts on Applied Economic R-esearch

”“Data scientists … spend from 50 percent to 80 percent of their time … collecting and preparing unruly digital data, before it can be explored for useful nuggets.” (— New York Times). The chartbookR package allows the convenient creation of economic and financial data chartbooks. It handles most of the data wrangling and can thus ...
[Read more...]
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