A reality-rooted perspective on “explainable AI” and what this means for the future of the field.
Researchers discuss how to extract valuable information from databases to aid decision making in emergencies, such as the current pandemic.
A team of data scientists has developed a general-purpose recommendation system for insurance based on Bayesian networks and deep learning.
Researchers study factors that affect the accessibility of ride-sharing programs such as Uber in Philadelphia.
By examining a wide selection of research works from the last two years, it was very clear that astronomers are using machine learning and AI as powerful discovery tools across a range of fields.
Machine learning technology has become mainstream in a large number of domains, and cybersecurity applications of machine learning techniques are plenty.
Crowdsourcing is an essential source of tourism information, especially in the accommodation sector.
The Internet of Things is the result of the convergence of sensing, computing, and networking technologies, allowing devices of varying sizes and computational capabilities (things) to intercommunicate.
Crowdsourcing opens the door to solving a wide variety of problems that previously were unfeasible in the field of machine learning, allowing us to obtain relatively low cost labeled data in a small amount of time.
Data mining and statistics, the roots and the path of development of statistical outlier detection and of database‐related data mining methods for outlier detection.