This blog post deals with solving fraud detection problems with graph machine learning. Learn how to load data, trainin and plot to find out who did it! It’s elementary, my dear reader.
Did you ever fall down some bottomless pit of bad data modeling? Our inter Adrian sure did, but he learned a lot from it - how to recognize the pitfalls and how to avoid them in the future! Hope his experience helps you… but let’s be honest, we never really learn from other people’s mistakes, so if you fall be sure to yell for help!
If you believe C++ is simply the best, you’ll be happy to hear that the new Memgraph C++ API enables you to effortlessly build query procedures, functions and other analytics tools using your favourite language. What are you waiting for? Code away!
We want to introduce you to Sasa, a frontend engineer on the Platform team responsible for developing and designing Memgraph Lab. In this blog post, Sasa talks about his onboarding experience and how he got his socks knocked off during the technical interview.
Summer has been a busy time for us. This rainy but extensive release of Memgraph brings you four significant features that are bound to make your life easier. As always, there are also bug fixes and smaller but nice improvements to avoid painful debugging moments as much as possible.
In recent months, users started to ask more frequently about the ability to run algorithms on a subgraph, and we in Memgraph listen to what our users need. Read more in this post How we designed and implemented graph projection feature
Our journey of creating an optimized shortest paths algorithm that returns all paths of same length. Starting from a MAGE query module and working within Memgraph's core, here is what we learned.
Security is playing a big role in the era of big data. To comply with the modern standards of privacy and compliance, we upgraded our security system to be able to authorize the graph on the node and relationship level. Find out how we did it here!
You can't always get what you want, but if you try sometimes, well, you might find, you get what you need. We took The Rolling Stones' advice and tried really hard to find the visualization tool that we need... It didn't really turn out as we wanted, or needed, but at least we had fun testing some software.
Are you tired of bland-looking graphs with limited relationship and node styles? Do you need some color and pictures in your graph life? So did we, until we created Graph Style Script! Now our graphs are bursting with life, and so can yours! What is GSS and how to use it, read this blog post to find out!
Orb is an open-source library developed by Memgraph you can use to visualize graphs by adding just a few lines to your frontend code. This blog post will show you all the cool features Orb offers and how to implement them in your project. Or don't and have slow and appalling graph visualizations - it's your choice. Seriously, use it... it's very easy and fun!
Sometimes in life, you have to roll up your sleeves and do the dirty work yourself. It's exhausting but pays off big time. That's exactly how it felt to build a visualization engine from scratch and then watch with what speed and elegance it renders complex graph structures. So if you are thinking about building a visualization engine, stop right there... we already did it! Pay attention!
Another Graph Data Zagreb is behind us. This time we had two conversations. In the first part, Manta gave us presentation about Data Lineage, and in the second part students who had their summer internships at Memgraph showcased the projects they worked on.
If you’re familiar with Memgraph or just started exploring its products, you must have heard about MAGE. But how did it all start, who came up with the idea, and who are the masterminds behind the product? Read more in this post!
Movie ratings from MovieLens are incoming, but you are still not sure what to watch over the weekend? Create your own movie recommendation system.
We have a special guest, Michaël Ughetto, a graph data scientist from AstraZeneca. Michaël will discuss how AstraZeneca ingests data sources in the Biological Insights Knowledge Graph (BIKG) and distribute it to data scientists and domain experts.