Tag: Machine Learning

Turning classes into inputs

Let’s face it, we all have worked on an ML project where we had to predict a ridiculously high number of classes. Large enough to make the number of observations per class into an embarrassingly small subset. Most people model these tasks as a multiclass classification problem where, for each input observation, we must predict […]

Written by on Sep 22, 2022

Privacy Preserving Machine Learning

Trip data is any type of data that connects the origin and destination of a person’s travel and is generated in countless ways as we move about our day and interact with systems connected to the internet. But why is trip data sensitive? The trips we take are unique to us. Researchers have found that […]

Written by on Aug 16, 2022

New internships in AI: Privacy-preserving ML and Similarity Learning

We are proud to share that NILG.AI has partnered with the Faculty of Engineering of the University of Porto (FEUP) through internships in AI as part of curricular units! We have received two new interns, Margarida Vieira and Beatriz Lopes; both enrolled in the Bachelor in Informatics and Computing, tackling two very distinct challenges with […]

Written by on Apr 21, 2022

We will be at VISUM Summer School

For the third time in a row, we are proud sponsors of VISUM summer school. VISUM is a worldwide reference summer school in Computer Vision and Machine Intelligence, attracting both experts and students to exchange experiences and knowledge in the field. VISUM has counted on the honor of receiving students from all corners of the […]

Written by on Apr 13, 2022

Teaching Models With Free Data

“The more I see, the less I know” might be a saying, but it does not apply to AI models. It’s well known that the performance of an artificial neural network is highly dependent on the volume and on the diversity of the data that was shown to the model. This happens because exposing the […]

Written by on Feb 23, 2022

WDL – Solving Social Problems Using Data Science

This article describes the key points of my participation at the 2021 Edition of the World Data League. The Tech Moguls Team, composed of me, Tiago Gonçalves, Tomé Albuquerque and Joana Morgado, from INESC TEC, finished second place in this edition. World Data League (WDL) is a Data Science competition where groups of Data Scientists […]

Written by on Nov 29, 2021

Multiple Product Forecasting in the construction industry

In this article, we will cover a use case in the construction industry related to forecasting the needed materials for construction and the time in which they will be required. In the construction industry, there is a lot of uncertainty between the order time and the time in which it is actually executed, due to […]

Written by on Nov 9, 2021

You Have the Right to Remain Silent

The Miranda warning prevents us from self-incrimination. You have the right to remain silent. Anything you say will be used against you. If we hold ML models accountable for their predictions, shouldn’t we at least grant them that right? Can we expect ML models to know everything? I guess we don’t! Moreover, it would be […]

Written by on Aug 2, 2021

Insights in AI applied to Credit Scoring

Having access to liquidity has been a major issue for humankind for financing both personal life aspects (e.g., housing, cars, college) and for business initiatives (e.g., starting, growing, and expanding a business). The amount of uncertainty that both faces of this exchange – i.e., the creditor and the prospective debtor – face are paramount. On […]

Written by on Jul 27, 2021

ML System Design: Federated Learning

NILG.AI, together with Neu.ro decided to try a format similar to a Reading Club, where the topic is not a specific paper but an entire research area. After a short discussion, we had a System Design part where the team described a specific use case to apply the new approach. Ideally, the discussion would stick […]

Written by on Jul 14, 2021