Regular blog readers will remember our seminar speaker competition from a few years ago.
If you did not already know
Jamovi The jamovi project was founded to develop a free and open statistical platform which is intuitive to use, and can provide the latest developments in statistical methodology. At the core of the jamovi philosophy, is that scientific software should be ‘community driven’, where anyone can develop and publish analyses, and make them available to a wide audience. jamovi for R: Easy but Controversial …
R Packages worth a look
Assisted Model Building, using Surrogate Black-Box Models to Train Interpretable Spline Based Additive Models (xspliner)Builds generalized linear model with automatic data transformation. The ‘xspliner’ helps to build simple, interpretable models that inherits informatio …
In case you missed it: December 2018 roundup
In case you missed them, here are some articles from December of particular interest to R users.
What to do when your training and testing data come from different distributions
By Nezar Assawiel, Machine Learning Developer, Founder at Clinical AI
Strata Data SF 2019 KDnuggets Offer
R Packages worth a look
Backward Procedure for Change-Point Detection (bwd)Implements a backward procedure for single and multiple change point detection proposed by Shin et al.
The cold start problem: how to build your machine learning portfolio
By Edouard Harris, Founder @SharpestMindsAI (YC W18).
Looking into 19th century ads from a Luxembourguish newspaper with R
The national library of Luxembourg publishedsome very interesting data sets; scans of historical newspapers! There are several data sets thatyou can download, from 250mb up to 257gb. I decided to take a look at the 32gb “ML Starter Pack�.It contains high quality scans of one year of the L’indépendence Luxembourgeoise (Luxembourguishindependence) from the year 1877. To make life easier to data scientists, the national libraryalso included ALTO and METS files (which is a XML schema that is used to describe the layout andcontents of physical text sources, such as pages of a book or newspaper) which can be easily parsedby R.
Robin Pemantle’s updated bag of tricks for math teaching!
Here it is! He’s got the following two documents: