Displaying 53 resources
Other
Communication and dissemination monitoring phase 1
This is deliverable 5.3 of the AI4REALNET project. This document provides an overview of the work developed so far in terms of communication and dissemination activities of the project, analysing the communication and the dissemination plans.
Other
Exploitation plan and strategy phase 2
This is deliverable 5.4 of the AI4REALNET project. This document outlines how AI4REALNET’s results will be brought to market, ensuring widespread adoption, long-term sustainability, and maximising the potential for project perpetuation.
Article/Books/eBooks
AI fundamental blocks – beta release
This is the deliverable 2.2 of the AI4REALNET project. This work package objective consists on developing the AI fundamental blocks for augmented decision-making, namely novel AI algorithms for large-scale sequential decision-making problems.
Certification
Online Course
Video/Webinars
Webinar "Distributed and Hierarchical Reinforcement Learning"
Seminar
Tutorial/How To/Guides
White paper
Oratione
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Video/Webinars
Webinar Towards Transparent, Safe and Trustworthy AI for critical infrastructures
This webinar focuses on the development of safe, explainable, and algorithmically transparent methods as part of the AI4REALNET project.
Video/Webinars
Webinar "Towards Transparent, Safe and Trustworthy AI for critical infrastructures"
This webinar focuses on the development of safe, explainable, and algorithmically transparent methods as part of the AI4REALNET project.
Software resources
Tutorial/How To/Guides
AI Fairness 360 (AIF360)
A GitHub repository for AIF360.
The AI Fairness 360 toolkit is an extensible open-source library containing techniques developed by the research community to help detect and mitigate bias in machine learning models throughout the AI application lifec
Software resources
Tutorial/How To/Guides
What-If Tool
A GitHub repository for the What-If Tool.
The What-If Tool (WIT) provides an easy-to-use interface for expanding understanding of a black-box classification or regression ML model.
Software resources
Tutorial/How To/Guides
Fairlearn
Fairlearn is an open-source, community-driven project to help data scientists improve fairness of AI systems.
Video/Webinars
Explainable AI for systems with functional safety requirements
Explainable AI (XAI) is vital for making AI decision-making processes transparent and understandable to human experts, and for ensuring safety and regulatory compliance.