Mobile phones, ATMs, modern cars, televisions, e-readers: none of them would work without software. The heart of software is formed by algorithms: step-by-step procedures to perform given tasks.
Common sense tells us that objects of comparable size should be equally hard to find. Yet, when searching inside a random network, surprises are awaiting . . .
In February 2014, a big bank in the Netherlands suffered from an internet banking malfunction which led many costumers to accidentally perform duplicate bank transfers.
Applications of machine learning models are everywhere, with many online platforms and major science fields using tools relying on machine learning. Take, for example, image recognition and computer vision. But did you know that the results of supposedly perfect and accurate machine learning models can be deceived by slight perturbations in the data?
This is a question I have been thinking about for the last two years. In this article, I will give a little overview of what I have discovered in that time.
Back in 2015, I joined the Movember health movement, a movement that you probably have heard of having something related to men growing a moustache. As a woman, you might imagine, I did not join for the moustache thing, but rather for the cause behind the moustache symbol, that is, raising awareness of prostate and testicular cancer.
