Transparency is of utmost importance when AI is applied to high stake decision problems where additional information on the underlying process beyond the output of the model may be required. […]
Fighting cervical cancer with Artificial Intelligence
In case you missed it. You may find below our talk on the Symposium on Bioengineering 2020 at FEUP. Also, we reply to some answers that we didn’t have time […]
Fairness in AI
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, […]
Applying geospatial data for Machine Learning, with a focus on social good
In partnership with Data Science for Social Good Portugal, we are launching a series of webinars in AI topics related to social good. The first talk was by Paulo Maia, […]
Experiment Management and Reproducible Research
In this tutorial, we will discuss how can we achieve reproducible data pipelines and research while keeping track of the experiments that lead to production Machine Learning models. We will […]
Who is tampering your meters? Fraud detection in Utilities
Meter tampering is a common threat to the business side of the utility services as well as a public security threat, incurring in uncontrolled tweaks that may increase the risk […]
Detecting Errors in Insurance Claims
Introduction and Motivation Insurance codes are used by people’s health plan to make decisions about how much your doctor and other healthcare providers should be paid. There is some variety […]
Thermal Imaging in AI
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 […]
Embedding Domain Knowledge for Estimating Customer Lifetime Value
As part of the rise of Deep Neural Networks in the ML community, we have observed an increasing fit-predict approach, where AI practitioners don’t take the time to think about […]
Appendix: Embedding Domain Knowledge for Estimating Customer Lifetime Value
This is an appendix to a blogpost previously published on Embedding Domain Knowledge for Estimating Customer Lifetime Value. We will describe some alternatives we considered for solving the proposed problem, […]