Awful AI: A curated list of scary usages of artificial intelligence

I found this amazingly horrifying list called Awful Artificial Intelligence: Artificial intelligence [AI] in its current state is unfair, easily susceptible to attacks and notoriously difficult to control. Nevertheless, more and more concerning the uses of AI technology are appearing in the wild. [Awful A.I.] aims to track all of them. We hope that Awful AI can be a platform to spur…

#100DaysOfCode: Machine Learning & Data Visualization

2018 seemed to be the year of challenges going viral on the web. Most of them were plain stupid and/or dangerous. However, one viral challenge I did like: #100DaysOfCode 1. Code minimum an hour every day for the next 100 days. 2. Tweet your progress every day with the #100DaysOfCode hashtag. 3. Each day, reach…

Beating Battleships with Algorithms and AI

Past days, I discovered this series of blogs on how to win the classic game of Battleships (gameplay explanation) using different algorithmic approaches. I thought they might amuse you as well : ) The story starts with this 2012 Datagenetics blog where Nick Berry constrasts four algorithms’ performance in the game of Battleships. The resulting levels…

Papers with Code: State-of-the-Art

OK, this is a really great find! The website PapersWithCode.com lists all scientific publications of which the codes are open-sourced on GitHub. Moreover, you can sort these papers by the stars they accumulated on Github over the past days. The authors, @rbstojnic and @rosstaylor90, just made this in their spare time. Thank you, sirs! Papers with Code allows you to quickly…

Visualizing the inner workings of the k-means clustering algorithm

Originally, I wrote this blog to share this interactive visualization of the k-means algorithm (wiki) which I was all enthusiastic about. However, then I imagined that not everybody may be familiar with k-means, hence, I wrote the whole blog below.  Next thing I know, u/dashee87 on r/datascience points me to these two other blogs that had already…

Tensorflow for R Gallery

Tensorflow is a open-source machine learning (ML) framework. It’s primarily used to build neural networks, and thus very often used to conduct so-called deep learning through multi-layered neural nets.  Although there are other ML frameworks — such as Caffe or Torch — Tensorflow is particularly famous because it was developed by researchers of Google’s Brain…

Privacy, Compliance, and Ethical Issues with Predictive People Analytics

November 9th 2018, I defended my dissertation on data-driven human resource management, which you can read and download via this link. On page 149, I discuss several of the issues we face when implementing machine learning and analytics within an HRM context. For the references and more detailed background information, please consult the full dissertation. More interesting reads on ethics in machine learning can be found here….

Computers decode what humans see: Generating images from brain activity

I recently got pointed towards a 2017 paper on bioRxiv that blew my mind: three researchers at the Computational Neuroscience Laboratories at Kyoto, Japan, demonstrate how they trained a deep neural network to decode human functional magnetic resonance imaging (fMRI) patterns and then generate the stimulus images. In simple words, the scholars used sophisticated machine learning to…

(Time Series) Forecasting: Principles & Practice (in R)

I stumbled across this open access book by Rob Hyndman, the god of time series, and George Athanasopoulos, a colleague statistician / econometrician at Monash University in Melbourne Australia. Hyndman and Athanasopoulos provide a comprehensive introduction to forecasting methods, accessible and relevant among others for business professionals without any formal training in the area. All R examples…