Caroline Mair

Are you interested in getting more insights and in learning more about the creative process of characterising data in terms of features that can help you reach better results when you are applying a data mining or machine learning algorithm? This is your chance then, as Sirris will be organising a second edition of this training session.

Nicolás González-Deleito

The Sirris Data Innovation team participated in the European Congress on Innovation in Textiles for Healthcare, which brought together key players from both the textiles and healthcare sectors, in order to present and discuss how innovations in these sectors can help to improve quality of life. Sirris gave a presentation on the challenges related to turning data collected via wearables and other sensors present in a user's environment into actionable information.

Caroline Mair

Before proceeding with in-depth data analysis, you first need to ensure that the data you have available is suited for solving your business problem. Data exploration is a first step in the data science workflow. It helps you to find out if the data you have available is suited for the problem you want to study. Our training session on data exploration helps you on your way.

Mathias Verbeke

Feature engineering is the process of extracting and selecting relevant, informative and distinguishing characteristics from your data, which can subsequently be used as input for a machine learning algorithm. As the quality of your features largely influences the quality of the results, feature engineering is one of the keys to success in successfully applying machine learning. While it is typically a creative and work-intensive process, understanding the methodology, tricks of the trade and common pitfalls can help you go a long way.

Nicolás González-Deleito

Building a digital coaching platform to help overweight people with a high cardiovascular risk lose weight and acquire and maintain a healthier lifestyle: this was the goal of WITH-ME. Sirris's main contributions in this project were related to the extraction of relevant information from subjective and objective data.

Mathias Verbeke

In collaboration with the EluciDATA user group, a number of concrete industrial use cases have been identified in the domains 'entity profiling and recommendation' and 'predictive analytics and forecasting'. For each of these use cases, a starter kit is being developed, to illustrate the potential of data innovation for a specific use case, in this way allowing companies to start with data innovation at a faster pace. As an example, a starter kit focusing on 'resource demand forecasting' is now available.

Caroline Mair

The exploitation of data collected on a fleet of machines is a real asset for maintenance and service personnel and, at a larger scale, for an entire company. The Sirris Data Innovation team will present the opportunities and the challenges related to this topic during a seminar on 24 October.

Caroline Mair

Data are flooding almost all sectors of our economy. That is why an increasing number of innovations is based on managing and interpreting (available) data, which are collected by various means. Are you eager to find out what data innovation can mean for your company, products, services and technology? Discover it in October at the Sirris’ mastercourse ‘Data-driven innovation beyond the hype’.

Omar Mohout

In the US a handful of former PayPal employees are behind the start of a number of large technology companies. Is our Belgian start-up ecosystem also concentrated around a number of key figures? Sirris went to find out.Looking like a bunch of gangsters, they appeared in Fortune Magazine in the US in 2007: ex-PayPal employees who, following the sale of the software company, put their weight behind technology stars such as YouTube, Yelp, LinkedIn, Yammer, SpaceX and Tesla Motors. They have been known as the ‘PayPal mafia’ ever since.Our country also has a blossoming start-up scene with a

Caroline Mair

In the context of the EluciDATA project Sirris will hold two master course sessions on 22 and 24 March. These sessions will provide you with a pragmatic and industry-oriented introduction to data-driven innovation.