In this post, I demonstrate a few techniques for plotting information from a relatively simple mixed-effects model fit in R. These plots can help us develop intuitions about what these models are doing and what “partial pooling” means. The sleeps...
A new minor version 0.2.3 of RcppCCTZ is now on CRAN. RcppCCTZ uses Rcpp to bring CCTZ to R. CCTZ is a C++ library for translating between absolute and civil times using the rules of a time zone. In fact, it is two libraries. One for dealing with civ...
Solution to Euler Problem 25 in the R language. What is the index of the first term in the Fibonacci sequence to contain 1000 digits? Continue reading → The post Large integers in R: Fibonacci number with 1000 digits, Euler Problem 25 appeared first on The Devil is in the Data.
Abstract We provide an interpretation for the confidence interval for a binomial proportion hidden as the transcript of an hypothetical statistical consulting session. This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. The markdown+Rknitr source code of this blog is available under a GNU General Public License...
The Windows edition of the Data Science Virtual Machine (DSVM), the all-in-one virtual machine image with a wide-collection of open-source and Microsoft data science tools, has been updated to the Windows Server 2016 platform. This update brings built-in support for Docker containers and GPU-based deep learning. GPU-based Deep Learning. While prior editions of the DSVM could access GPU-based capabilities...
Neural network have become a corner stone of machine learning in the last decade. Created in the late 1940s with the intention to create computer programs who mimics the way neurons process information, those kinds of algorithm have long been believe to be only an academic curiosity, deprived of practical use since they require a
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Dear Fantasy Football Analytics Community, Four years ago, we released web apps to help people make better decisions in fantasy football based on the wisdom of the crowd. Over the past The post Call for Help: R/Shiny Developer appeared first on Fantasy Football Analytics.
I'm excited to announce my DataCamp course on importing and managing financial data in R! I'm also honored that it is included in DataCamp's Quantitative Analyst with R Career Track!You can explore the first chapter for free, so be sure to check it out!Course DescriptionFinancial and economic...
Nic Crane, Data Scientist The agenda for EARL London has just been...
Analytic administrator is a role that data scientists assume when they onboard new tools, deploy solutions, support existing standards, or train other data scientists. It is a role that works closely with IT to maintain, upgrade, and scale analytic environments. Analytic admins have a multiplier effect - as they go about...
Smoothing a time-series with a Bayesian model Recently I looked at fitting a smoother to a time-series using Bayesian modelling. Now I will look at how you can control the smoothness by using more or less informative priors on the precision (1/varianc...
For the past four years, recruiting firm Burtch Works has conducted a simple survey of data scientists with just one question: "Which do you prefer to use — SAS, R or Python". The results for this year's survey of 1,046 respondents are in: R: 40% (2016: 42%) SAS: 34% (2016: 39%) Python: 26% (2016: 20%) Compared to last year's...
The first part of this post is a quick update on Tony Cooper’s of Double Digit Numerics’s volatility ETN momentum … Continue reading →
Great painters can teach us a lot about how to compose a good palet for our plot. That is why we look here at a way to algorithmically derive a colour palette from any jpeg image. Application of derived palettes on ggplot is also showed. The post How to build a color palette from any image with R...
Scatter & Bubble chart This is the third part of our data visualization series and at this part we will explore the features of two more of the charts that googleVis provides. Read the examples below to understand the logic of what we are going to do and then test yous skills with the exercise
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Back in February, I wrote some R code to analyse tweets covering the 2017 Lorne Genome conference. It worked pretty well. So I reused the code for two recent bioinformatics meetings held in Sydney: the Sydney Bioinformatics Research Symposium and the VIZBI 2017 meeting. So without further ado, here are the reports in markdown format, … Continue...
Below is the latest update to The Popularity of Data Science Software. It contains an analysis of the tools used in the most recent complete year of scholarly articles. The section is also integrated into the main paper itself. New … Continue reading →
Sorry for the clickbait title. Couldn't resist. The post Counterintuitive problem: Everyone in a room keeps giving dollars to random others. You’ll never guess what happens next. appeared first on Decision Science News.
Traditionally, statistics like wOBA (weighted on-base average) have been calculated using league averages. While building the baseballDBR package, I thought it would be interesting to group the American and National when making wOBA calculations. In th...
A year ago, I used Google’s Vision API to detect brand logos in images. Since then the DIY deep learning possibilities in R have vastly improved. With the release of Keras for R, one of the key deep learning frameworks is now available at your R fin...
In order to get the discount, simply click choose a link below and when paying use the promo code: J17UDEMY203 Udemy is offering readers of R-bloggers access to its global online learning marketplace for only $10 per course! This deal (offering over 50%-90% discount) is for hundreds of their courses – including many R-Programming, data science, machine learning etc. Click here to browse ALL...
The sparklyr package (by RStudio) provides a high-level interface between R and Apache Spark. Among many other things, it allows you to filter and aggregate data in Spark using the dplyr syntax. In Microsoft R Server 9.1, you can now connect to a a Spark session using the sparklyr package as the interface, allowing you to combine the data-preparation...
In this post I explore two different methods for computing the relative importance of predictors in regression: Johnson’s Relative Weights and Partial Least Squares (PLS) regression. Both techniques solve a problem with Multiple Linear Regression, which can perform poorly when there are correlations...
When analyzing data, you can start by thinking about how to classify the data you have according four main scales of measurement.
Partial Least Squares (PLS) is a popular method for relative importance analysis in fields where the data typically includes more predictors than observations. Relative importance analysis is a general term applied to any technique used for...
In this post we will see how to include the effect of predictors in non-linear regressions. In other words, letting the parameters of non-linear regressions vary according to some explanatory variables (or predictors). Be sure to check the first post on this if you are new to non-linear regressions. The example that I will use Related Post
To post your R job on the next post Just visit this link and post a new R job to the R community. You can post a job for free (and there are also “featured job” options available for extra exposure). Current R jobs Job seekers: please follow the links below to learn more and apply for your R job of interest: Featured Jobs Full-Time Data analyst...
Bias vs Variance tradeoff is always encountered in applying supervised learning algorithms. Least squares regression provides a good fit for the training set but can suffer from high variance which lowers predictive ability. To counter this problem, we can regularize the beta coefficients by employing a penalization term. Ridge regression applies l2 penalty to the
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I started writing my first package as collection of various functions that I needed for (almost) daily work. Meanwhile, packages were growing and bit by bit I sourced out functions to put them into new packages. Although this means more work for CRAN members when they have more packages to manage on their network, from 
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