Quantifying Londoners change in fitness habits during lockdown

With people being urged to stay at home during the Covid-19 outbreak, gyms closed, and social distancing measures in place, it’s safe to say that fitness and workout trends have changed along with other aspects of daily life. Using data from Twitter, we set out to investigate the popularity of certain fitness related keywords, before…

Comparison between Naïve Bayes and Logistic Regression

Naïve Bayes and Logistic regression are two popular models used to solve numerous machine learning problems, in many ways the two algorithms are similar, but at the same time very dissimilar. This blog post highlights some of the similarities and dissimilarities between these two popular algorithms. To start off, let’s remind ourself how these two…

Three things to know about machine learning

Machine learning is about learning from dataThe first thing to know about machine learning is that it’s often referred to as Artificial Intelligence by the popular media and they make it sound like the computer has become super intelligent and self-aware. In reality, machine learning – or AI – is just about learning patterns in…

Reading RR intervals from EliteHRV with Pandas

Heart Rate Variability (HRV) is a measure of the time interval between each heart beat and is a measure that in contrast to beats per minute can quantify the variation between each heartbeat. This blog post explains how HRV readings done with the mobile application EliteHRV can be read and plotted with Pandas and Python.…

Fear not – AI won’t take over in the imminent future

Within the recent decades, and even centuries undertakings done by humans have seen automation and machine replacements. The affected people and groups have subsequently transitioned to new occupations and the world has moved on. Such as when machines took over as the main driver within the textile industry during the Industrial Revolution (Wikipedia, 2016) or…

Ethical challenges that Data Science faces

Challenges such as data quality, models, algorithms, processing power and processing speed are well spoken challenges within data science, but one highly important challenge that rarely get mentioned is the ethical aspect of Data Science (Presthus, 2012). With the rise of even more connected devices, digital services and automated systems the amount of data that…