Tag: Machine Learning

How to deal with the annoying implications of changing data sources

Let’s discuss a common scenario in AI consulting. The client provides access to data sources in formats such as CSVs or databases that aren’t in a production environment. Why? Usually, they’re exploring the value of the project, do not want to disclose too much data and want to prevent technical problems from happening at the […]

Written by on Nov 20, 2022

Stop removing outliers just because!

Outliers are data points that stand out for being different from the remaining data distribution. An outlier can be: An odd value in a feature A data point distant from the centroid of the data A data point in a region of low density, but between areas of high density. Suppose you have been working […]

Written by on Nov 14, 2022

Detecting duplicates in text

A common use case seen across several industries is the creation of systems capable of detecting the similarity between pairs of objects – images and texts. For example, duplicate detection in marketplaces, or recommendation systems that show similar objects to the ones the user has searched for, can use such systems. They can also be […]

Written by on Oct 25, 2022

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