Tag: AI4tech

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

A new era has arrived for NILG.AI

Happy birthday! Today is NILG.AI’s fourth anniversary. Happy birthday to us! For most humans, birthdays are a synonym for getting older and leaving the good days of the youth behind. For companies, they are a moment to reflect on everything we achieved, recognize how far we have come, and envision how far we will go. […]

Written by on Sep 5, 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

Local vs. global optimization

Is the fastest route always the best? This article may give you a different perspective if your answer is yes. Normally there are multiple ways to tackle a given problem or task, and the optimization field is no different, as there are different approaches we can take to find an optimal solution. The choice of […]

Written by on Jun 23, 2022

Achieving diverse product recommendations

In this blog post, you’ll learn about some examples of decision processes you can use in recommender systems: do you see any usage for recommending less popular products as a way to improve your business? You will see it now! The Use Case Let’s imagine a use case where you are building a MOOC platform […]

Written by on May 25, 2022

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

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