The “pomodoro technique” is a simple time management method, which requires a robust, simple-to-use timer, which doesn’t distract from the task at hand. For the third version, I constructed a plywood case to house the microcontroller, the 4-digit display, and the two buttons to control the timer.

Learning is often a process of rediscovering things. I enjoyed this process recently when trying to solve a combinatorial puzzle, in the pub, in the bus, and at home. A tale of allowing myself to explore, to tinker, and to be awed by the great thinkers of long gone times.

UK keyboards, for good reasons, do not come with keys for ÄÖÜ. Here is a quick-and-dirty fix to customize the xkb symbols map, tested on on Arch Linux.

The “pomodoro technique” is a simple time management method, which requires a robust, simple-to-use timer, which doesn’t distract from the task at hand. After the first prototype with the ATmega32-based RN-Control v1.4 experimental board, I built another prototype: this time with a 4-digit display.

The “pomodoro technique” is a simple time management method, however in my opinion completely lacks support from something essential: a robust, simple-to-use timer, which doesn’t distract from the task at hand. Thus, I built a prototype with the ATmega32-based RN-Control v1.4 experimental board.

If you ever wanted to use the right Ctrl button in Ubuntu 20.04 as an i3 modifier, and struggled with xmodmap, try editing the modifier mappings directly in /usr/share/X11/xkb/symbols/pc. It’s dirty, and may fail during software update─but meh until then it appears to work.

If you are a runner and desperate for a quick-and-dirty formula you can use in a Google Spreadsheet to convert running pace from minutes per mile into minutes per kilometer, this nerdy post will give the formula to you.

How to load Strava activities into Google Cloud BigQuery and visualizing the activities with Google Data Studio? This article is for (hobby) athletes interested in taking a walk through the Strava API, Google Cloud Platform and Google Data Studio; showing how to gain the freedom to explore and visualize the data you have been sweating for over years.

A review of Scott Page’s Model Thinking course, which has been overall entertaining, inspiring, informative albeit at times a bit repetitive when going through arithmetics. If you are interested in trying to make sense out of the complex world around you, this course might be for you.

Assume you are practicing for an exam. You could spend all your time left until the exam practicing (possibly too much), or you could spend almost no time practicing (likely too little). So how do you know when enough is enough? When can you stop practicing and yet be confident that you will pass the exam?

Today, I’ll demo how to train a logistic regression model in BigQuery ML. That is Machine Learning models written in SQL, and executed in BigQuery.

OpenAQ is publishing real-time air quality data from around the world to BigQuery. Today, I have poked around in the dataset to inspect air quality from many places of the world.

Whether you are an event organizer waiting for participants to turn up or whether you are a bus driver waiting for passengers running to catch the bus, there is a dilemma: if you are so kind and wait for everyone to arrive, you make everyone else wait. Let’s explain the dilemma with probability theory.

How do you analyse Strava activities—such as runs or bike rides—with Colab, Python, Pandas, and Matplotlib? In my fourth article on this topic, let’s invite scikit-learn and NLTK to the party, and apply some Machine Learning.

How do you analyse Strava activities—such as runs or bike rides—with Colab, Python, Pandas, and Matplotlib? In my third article on this topic, I am demonstrating how to visualize the data in different ways.

How do you analyse Strava activities—such as runs or bike rides—with Colab, Python, Pandas, and Matplotlib? In my second article on this topic, I am demonstrating how to group and aggregate the data in many different ways.

How do you analyse Strava activities—such as runs or bike rides—with Colab, Python, Pandas, and Matplotlib? In this post, I am demonstrating how to get started, and will give you a taster of what is possible with this state-of-the-art technology for data analysis.

I discovered a misleading infographic on mortality cause by gender in the OECD report “Health at a Glance 2017” while working on a course assignment. A few notes on how not to do bubble charts.

How do you teach a computer to play games? I took a classic brute-force approach along with some techniques to make the search for a good move faster. Can you beat the machine?

The opportunities created by the advance of technology and the efforts of people are amazing. In this post, I’ll show how to take advantage and use the Mapswipe App as a first step to gain valuable insights for NGOs operating in places of the world for which there is no proper map yet.

Habits are an important key to success. But how do we establish a habit? How do we know whether our perception aligns with reality? How do we decide about the next change to make? Did we succeed? I want to know. A reflection on habits, insights from data using running as an example.

There are places on our planet where people live but there is no map. How are NGOs like Médecins Sans Frontières (MSF) supposed to do field work if they don’t know where people live, how many, how to get there? The Missing Maps project is addressing the issue via crowdsourcing. I gave it a try, and here’s what I think.

Let’s face it. Air quality in London is quite poor. You don’t need technology to notice. As soon as you reach the country side, the difference is usually very apparent. I will soon get hold of an active sensor that transfers carbon monoxide readings to my phone in real-time. Interesting: the sensor is powered only from energy harvested from wireless and broadcast networks. Energy from thin air!

A visit to Milton Keynes gave me a brief look into former codebreakers’ life at Bletchley Park during World War II. The exhibition also featured a rebuilt exemplar of the bombe, an electromechanical machine that played a role in breaking the code of the Enigma. I got fascinated for several reasons.

Persistence paid off. The little, remaining work on my Master’s thesis at KTH is finally completed. I can hardly remember touching a subject at university that was as demanding and as satisfying as the research on how to segment moving objects in videos taken by a RGB-D camera. Thanks to everyone who helped me with this mission.