At dataroots, we like to present our service portfolio by means of a burger. Like a burger, the ‘pièce de résistance ‘ is the Artificial Intelligence value-chain, with data pipelines transporting & providing quality data from source to model, simple or complex models mashing the data into insights and finally integration of those insights into the day to day business processes to put these hard earned insights to work. Also like a burger, the way to facilitate the efficient consumption of the ▋

Since 2020, dataroots participate in the AI Song Contest. Since the contest is coming soon and the team is working hard, we thought to tease with our previous participations! 6 dataroots colleagues group together with only one mission: generating fully automated songs by clicking a button! The final algorithm generates songs by traversing the shortest distance in MIDI harmonies sampled by Variational Autoencod▋

Causal inference is used to determine whether an action on a selected population is efficient and by how much. It is extremely useful to evaluate the average treatment effect of a campaign. For this, you need to compare the outcome difference on a treatment and on a control group. In this post, we explain techniques that can be used to evaluate an action even when a proper control group does not exist. We will explain how causality can still be inferred and tested and how much we can deduct fr▋

This blogpost will give you a gentle (re)introduction to the idea of matrix factorization, an enormously useful technique in statistics and machine learning. Matrix Factorization Matrix factorization is a technique to decompose or factorize a matrix into a product of more fundamental matrices. If that sounds a bit confusing, it's analogous to factorizing a number: 48=4×12 or 48=6×8. Of course, a matrix is more complex than a number, so many kinds of factorization are possible. Perhaps the easi▋

Machine learning engineers are at the intersection of programming (computer science), math/statistics/machine learning and domain knowledge/communication. Although a lot of progress has been made in the first two, their advances are constrained by the ability to convey their results to the business owners of a problem. Graphical representation can be of enormous help to bring over complex results. In this blogpost, we discuss latest trend in visualisation of statistical results. State-of-the -ar▋

Campaigns you said? Great but which one? Multiple ways exist to nudge customers: for instance calling, sending out emails, offering discounts, etc. The channels are various and the content of the marketing messages are even more diverse. In this article we explain how to optimize a marketing campaign and what to do when you did not implement the ideal strategy but have data that can help you derive important insights. From churn prediction to business value Not so long ago, in a previous post▋

Over the weekend I had the pleasure of talking to Gertrude Poirot Torricelli III, long for GPT-3. Her insightful advise and hopeful views on the future of society and the world at large inspired me to share her musings with the rest of you. She was very open to this idea and I will be sharing her advise in quote form daily during the week of April 11th, 2022. All quotes will be collected down here. 👇 Monday Tuesday Wednesday Thursday Friday That wraps up this non-existent quotes series! ✅ �▋

As a growing data consultancy boutique, we get more and more questions to review and architect data platforms. While growing, we are also maturing the architecture practice at Dataroots. What is Architecture? We can obviously not discuss architecture without some reflection on the term itself in the context of ICT solutions in general, and data platforms specifically. A topic which immediately proves to be not that easy to grasp. When brainstorming the subject, we easily talked about the respon▋

You hear more and more that technology in general is not so eco friendly. What about AI? Is it also not so eco-friendly? What is the impact of developing AI models and how good is AI for the planet? With this article, we try to demystify and understand the impact of AI on the planet and how this could be reduced. What are the resources needed to build an AI? To build AI models, requires a lot of resources, especially if you are building models like Bert, GPT, or in general, deep neural net▋

You love Matplotlib cause it's easy to use and you can generate plots quickly? It's now possible to do these Matplotlib exact same plots with dataroots theme with Rootsstyle ! Rootsstyle works with any visualization tools that builds upon Matplotlib (seaborn, pandas). Check it out !▋

If you ever took a look into Natural Language Processing (NLP) for the past years, you probably heard of transformers. But what are these things? How did they come to be? Why is it so good? How to use them? A good place to start answering these questions is to look back at what was there before transformers, when we started using neural networks for NLP tasks. Early days One of the first uses of neural networks for NLP came with Recurrent Neural Networks (RNNs). The idea there is to mimic huma▋

When you start integrating data into your marketing strategy, the first questions that needs to be answered are often: who’s going to churn in the next couple months? To whom should we best sell what product? Does that person need this product? To answer these types of questions one can build a model based on historical data. We look for customers that demonstrated the desired behavior in the past (churn, buying a product, etc) and how they looked like (characteristics and behavior). The assump▋

Want to discover if a career in AI is something for you? Apply for one of our cool internships or propose your own! We are already planning the internships of next year, here is a sneak peak into what it entails 🤖 Looking for an internship? Internships are the perfect way for you to see if you would like to pursue a career in AI and for us to see if there’s a match for a long-term collaboration! There is not enough time in a human life to develop all the cool ideas that we have in mind so it▋

The problem. Artificial intelligence (AI) is driving the rapid transformation of industries. However, the exponential rate of that transformation is difficult to manage for legislators. Moreover, there is no industry standard to ensure AI is safe and beneficial. New applications are introduced at breakneck speed, oftentimes without sufficient consideration of their potential societal impact. AI promises to enable the scaleable automation of almost any decision-making system. In doing so, we amp▋

Deep neural networks offer unparalleled performance for many applications, but running inference can be resource-intensive. Model optimization comes in to help here, reducing disk storage, memory usage or compute requirements. This can be useful for deployment on the edge (to run models where it otherwise would not be possible), as well as for the cloud and on-premise (to run models faster, or allow more models te be stored in-memory simultaneously). Moreover, reduced energy requirements of opti▋

Last week, the winter Olympics in Beijing came to an end. For Belgium, this meant a successful edition with one female (Hanne Desmet) and one male (Bart Swings) medal. Belgian medals at the Winter Olympics are pretty rare anyway but the medal of Hanne Desmet was the first Belgian female one since the games of 1948 in Sankt Moritz! At dataroots, we highly value diversity, putting the topic regularly on the agenda to see if everybody thinks we’re on the right track. The past decades, the topic ha▋

Unboxing an embeddable analytical database. DuckDB is a recent addition in the analytical database world. And it takes an interesting approach: it wants to be the SQLite for analytics. DuckDB was developed by Mark Raasveldt and Hannes Mühleisen, two database researchers at the Centrum Wiskunde & Informatica (CWI) in Amsterdam, the Dutch National Research Institute for Mathematics and Computer Science. CWI is not just any research institute. For a few decades now, the team has been pushing the ▋

As we alluded to in our trends post , the number of researchers, developers and companies that focus on eXplainable AI (XAI) is growing faster each year. 💡XAI is an umbrella term for methods, algorithms and tools that increase insight into the inner workings of AI. This is in contrast wit▋

Matching theory (a branch of game theory) is a mathematical framework attempting to describe the formation of mutually beneficial relationships over time. What other topic could we possibly have chosen for Valentine's day? Actually, this is a very serious and important field of research in economics. And, in 2012, Alvin Roth and Lloyd Shapley got awarded a Nobel prize ▋

> Notion ➕ Great Expectations = 🚀 If you've ever heard of or used Notion (specially their databases) and Great Expectations, you can already imagine what this is about 😉. If not, find a quick ELI5 below: See our Github for more technical details and detailed instructions. 👶 ELI5: Great Expectations > "Great Expectations is a shared, open standard for data quality. It helps data teams eliminate pipeline debt, through data testing, docu▋

eXplainable AI or XAI is crucial to ensure stakeholder and public trust, as well as reliability, particularly in high-stake contexts where AI decisions can impact lives. Open-source contributors, researchers & companies are stepping up their game by providing ever-more ambitious and inventive methods to ensure transparent, interpretable and ultimately, explainable AI. As a consequence, XAI methods are sprouting up like mushrooms, meaning that the decision on which method to use is becoming inc▋

If you're not new to Python and data science, you probably heard of Jupyter notebooks . But if you haven't, here's the gist: it's an interactive environment, meaning you can run little bits of code and see the output, store variables in memory, etc. That makes notebooks a good tool for experimentation, reporting and visualizations. And because of that, it's a popular tool of choice for data science in general. And this is why you see a lot of notebooks in places like Kagg▋

Foreword In this post, we have gathered our experts’ views on new developments in AI. However, AI is a broad field and we do not pretend to have a complete understanding of the whole landscape. Our view is necessarily biased by our activities as an AI service provider and our Belgian market presence. Bearing this in mind, we examine different trends that we have spotted in AI across industries, research, tooling and much more. The goal of this article is to get an overview of the landscape and ▋

🙌 An article that our very own Tim Leers co-authored just got released. A snippet of the summary: > Engagement and training of community health workers (CHWs) have demonstrated their value in different conditions. Despite repeat epilepsy trainings of CHWs in Northern Rwanda, the treatment gap remained high. We hypothesized that effectiveness of CHWs on mobilization of patients living with epilepsy (PwE) could be improved using a va▋

Watch our experts share our views on : * What type of data do we currently work with? * How are the AI use cases evolving? * How much time does it take to leverage value from AI/data? * What has been the biggest evolution in infrastructure to support the AI cases * Where is the market in terms of AI adoption and maturity? * What is the role of the EU citizens, how are they included in AI projects/development?▋

> Why would the chef give away the recipes for the dishes he is famous for? What does the engineer achieve from sharing his schematics for that new technological marvel? Working open source is like sharing your secrets. These contemplations are often pronounced by people outside or not familiar with software development. Let’s have a look at a couple of examples of why and where Open Source proves its value in our day-to-day business. Essential ingredient Free Open Source Software (FOSS) is an▋

Soo... I got asked by Virginie Marelli to explain what cheek is. Here goes: cheek is an approach at building a simple job scheduler that…▋

What was the last time you actually set a foot in a bank? How often do you still pay with cash? I honestly cannot remember the last time I…▋

🎉 Murilo Cunha released his first official version of databooks earlier this month. databooks is a package that eases the collaboration…▋

Entering 2022, we also look back on an incredibly active year of sports. Together with the company, our team events grew and so the amount…▋

There is no doubt that there resides a lot of value in your data! There is probably lots of it in your company, together with some smart…▋

Introduction and Context Anyone who has spent some time in Belgium/Flanders probably knows that road cycling is very popular around here…▋

The AI environment is becoming increasingly mature. Once hard to crack processes are now being automated in no time and it won’t be long…▋

Let's imagine you are a freshly recruited Data Scientist. During one of your stand-up, your product owner gives you a couple of tasks that…▋

AAPI, de digitale planningstool voor horecaondernemers, schuift aan tafel met de Leuvense AI-expert Dataroots en het visualisatieplatform…▋

If you are working with a lot of data like we do at dataroots then it is highly possible that you encountered your fair share of bad…▋

Over the past decade, data driven decision algorithms have become more and more performant and prevalent, but also complex. They are not…▋

While the advent of advanced artificial intelligence (AI) systems in our daily lives is an absolutely thrilling prospect (and increasingly a…▋

As the surge in gas and electricity prices intensifies with the UK and European gas prices even closing at ten times their level from the…▋

Before we dive in, what is MLOPs? There is much to say about it, but much like me, I'll keep this short and sweet. As you could've guessed…▋

You all know that datarootsians are excellent data athletes. Olympics athletes train with weights, we evolved past that mere display of…▋

Ray is such a cool distributed computing library that it makes me weep for joy. It is not only cool for batu + ray = baturay but it is also…▋

Who hasn't heard of data quality? If there is a topic that comes up again and again lately it seems to be data governance where data quality…▋

Why does it matter Data, AI, Machine Learning, etc. are complicated terms, and many organizations still struggle to implement and gain real…▋

Toepassing data science in deze context primeur voor Belgische multinational Puratos bereikt nieuwe hoogtes in natuurlijke…▋

Mobile application enriches data from different bank accounts and shares profits with its users The Belgian mobile app Cake bundles and…▋

Artificial intelligence (AI) and data-driven solutions have been on the rise for quite some years now and their many applications became an…▋

AI is everywhere. Overtuigd van de kracht van data, trekt de moderne bedrijfswereld nu resoluut de kaart van artificiële intelligentie. De…▋

The rise of artificial intelligence is unstoppable. Not only are businesses appealing to AI more frequently than before to boost their…▋