Machine Learning (ML) engineering and software development are both fundamentally about writing correct and robust algorithms. In ML engineering we have the extra difficulty of ensuring mathematical correctness and avoiding propagation of round-off errors in the calculations when working with floating-point representations of a number. As such, ML engineering and software development share many challenges… and some of the solutions to these. Concepts like unit testing and continuous integration rapidly found its way into the jargon and the toolset commonly used by data scientist and numerical scientist working on ML engineering.

What’s the point in downloading the app from the store when you can do the same thing in the browser? I’m a product designer at trivago, and would like to share some insights into one of our biggest projects we tackled in the last period. Designing trivago’s new mobile app!

It is not everyday that you get to chat face to face with the creator of a highly relevant open source project. Accordingly, we were highly anticipating a certain visit in mid-October, 2018.

Sometimes, when I look back over the time I have spent working at trivago, I see how it changed my life and how lucky I have been to get the chance to work among this amazing community, to live and to learn with them. I look back and see a younger version of myself looking desperately for something different and, by just sheer luck, getting it.

It has been a couple of months since Kyle, author of the “You Don’t Know JS” series, visited our trivago headquarters and gave us a wonderful JavaScript workshop. It was such an enjoyable week, being able to meet Kyle in person and walk through his thinking behind the materials. trivago hosts internal workshops and meetups regularly and offers numerous learning opportunities to the employees throughout the year. This time, we decided to do it a little differently.