� Dan Sholler, rOpenSci Postdoctoral Fellow

By Kayla Matthews, Productivity Bytes

This year at NeurIPS 2018 the Symposium on Advances in Approximate Bayesian Inference discussed challenges and advances in approximating probabilistic inference in rich models. It was a genuinely exciting program!

Many (if not most) tech communities have far more representation from men than from women (and even fewer from nonbinary folk). This is a shame, because everybody uses software, and these projects would self-evidently benefit from the talent and expertise from across the entire community. Some projects are doing better than others, though, and data scientist Reshama Shaikh recently published an in-depth comparison of the representation of women in the R any Python communities.

This post is the second of my #saxeburg-series, for young entrepreneurs (or the young at heart), in which we’ll learn about Neo4j and have some fun at the same time. How? By building our own Neo4j-powered mobile game.

Activation Regularization for Reducing Generalization Error in Deep Learning Neural Networks

The ggQC package is a quality control extension for ggplot. Use it to create XmR, XbarR, C and many other highly customizable Control Charts. Additional statistical process control functions include Shewart violation checks as well as capability analysis. If your process is running smoothly, visualize the potential impacted of your next process improvement with a Pareto chart. To learn more, read on!

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 soon I realised, that it will be much easier to share and improve those functions, if they are within a package. Up till the 24th December I will present one function each day from helfRlein. So, on the 5th day of Christmas my true love gave to me…

This post is the first of my #saxeburg-series, for young entrepreneurs (or the young at heart), in which we’ll learn about Neo4j and have some fun at the same time. How? By building our own Neo4j-powered mobile game.

The countdown to year’s end is on, and we’ve begun collecting expert opinions on 2018’s main developments and 2019’s key trend predictions. We also share a great set of deep learning cheat sheets, a collection of the best tools, languages, and frameworks, see how to build a machine learning team when you aren’t a tech giant, and get schooled on how to choose the best machine learning course. Enjoy!