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Data Scientist
Solving AI-based problems as brain teasers is one of my favorite tasks, from problem formulation to solution implementation. Tell me about the next goal for your business, and let’s discuss strategies to achieve it.
Apr 10, 2023 in Technical
The Problem What do you do when the model is underperforming? When the models’ performance does not meet our expectations, we usually spend time searching for the flaws, selecting and analyzing the cases where it failed to understand why it happened. Then, we try to apply more robust solutions, train, test, and repeat. In some […]
Nov 14, 2022 in Technical
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 […]
Feb 23, 2022 in Technical
“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 […]
Aug 2, 2021 in Technical
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 […]
Jun 1, 2021 in Industry Overview
At NILG.AI, our motto is “Unlocking business capabilities using Data Intelligence”, since we see Artificial Intelligence as a powerful tool designed to maximize the potential of human activity. A lot of fields have been taking advantage of the AI revolution creating more efficient systems able to get more accurate results while saving time and operation […]
Feb 17, 2021 in Technical
In the good old days, working as a Machine Learning Engineer meant working 95% of the time on feature engineering and 5% on training models with the extracted features. This was a manually intensive and time-consuming process, that usually led to inflexible proofs of concept that could hardly be adapted to new settings. Fortunately, Deep […]
Aug 18, 2020 in Webinar
In partnership with Data Science for Social Good Portugal, we are launching a series of webinars in AI topics related to social good. The second talk was by Francisca Morgado, on the 29th of July, with the topic “Fairness in AI”. In case you weren’t able to register in time or attend the talk, it […]
Apr 24, 2020 in Industry Overview
Artificial Intelligence (AI) is one of the current hottest issues, intersecting many fields of interest. With the dissemination of this concept, the expectations about its potential grew a lot among the society. Some people look at AI as a set of mechanisms that can improve people’s intelligence, increasing the human activities performance, others look at […]
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