m-zine

DjangoCon Europe is run by the community for the community: which is what makes it just the kind of event we absolutely love to attend. It was a fun event that gave us a fresh perspective on the current state of Django… and the ramen was pretty good too!

Women are still under-represented in STEM subject studies and in technical positions in the workplace. Employers who want to achieve gender equality and have more diverse workplaces struggle with a lack of applicants.

On November 7–8, three of our team members traveled to San Francisco for the GraphQL Summit. Was it worth the jetlag? Absolutely. We had the opportunity to listen to presentations from industry leaders like AWS, Apollo, GitHub, Netflix, and Braintree, among many others.

Let’s face it, the UI and UX may sometimes still be a bit clunky in Open Source, but we can no longer deny the fact that the entire market is moving toward an open model. 97% of companies now run at least some Open Source software.

Learn how to build powerful recommendation systems by combining user preferences with collaborative filtering. This article explores practical techniques for achieving accurate user matches and smart product bundling. It will help your system to deliver personalized and practical recommendations.

A new year means new opportunities. We are fully focused on how we can roll with the big underlying e-commerce trends, as well as looking at emerging technologies which can enhance our business. Here is our take on what will shape e-commerce in 2019.

The key to exceptional technical solutions is a solid brief and ongoing, high-quality communication. Our collaboration with Lulu showcases an effective template for remote teams working across continents under time pressure in agile methodology.

Nearly 2,000 attendees, mostly women, gathered in Amsterdam for the 2018 edition of the European Women in Tech conference, which celebrates diversity in the fast-growing tech industry. Here’s what we learned from the event.

We’re going to talk about explicit and implicit data in Recommendation Systems, especially looking at the problems that negative or unclear responses can cause. It helps to know something about the subject upfront.