TransferLab Training: Methods and issues in explainable AI

Empowering professionals to develop and apply latest AI technologies responsibly.We embrace collaboration, knowledge sharing, and open source principles, creating an environment where everyone can actively contribute to AI development and decision-making.We’re dedicated to creating a future where AI is accessible, inclusive, and beneficial for everyone.Come join us on this journey!

appliedAI Institute for Europe gGmbH

TransferLab Training - Methods and issues in XAI

Join our series of workshops designed for ML practitioners who aim  to make their models better understandable for themselves and decision makers.

A two-day workshop for ML practitioners wishing to make their models better understandable for themselves and decision makers.Safety and reliability concerns are major obstacles for the adoption of AI in practice. In addition, <a href="https://digital-strategy.ec.europa.eu/en/policies/european-approach-artificial-intelligence" title="https://digital-strategy.ec.europa.eu/en/policies/european-approach-artificial-intelligence" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">European regulation</a> will make explaining the decisions of models a requirement for so-called high-risk AI applications.When models grow in size and complexity they become less interpretable. Explainability in machine learning attempts to address this problem by providing insights into the inference process of a model. It can be used as a tool to make models more trustworthy, reliable, transferable, fair, and robust. However, it is not without its own problems, with algorithms often reporting contradictory explanations for the same phenomena.ContentsWe consider the machine learning pipeline under the lens of explainability. Through a series of hands-on use case examples the participant will be introduced to methods for:<ul><li>Exploratory data analysis</li><li>Feature selection and engineering</li><li>Model selection</li><li>Model evaluation and visualization</li><li>Model interpretation and explanation</li></ul>These are tailored to improve the understanding of why a model acts as it does.Check out the <a href="https://transferlab.ai/trainings/explainable-ai/" title="https://transferlab.ai/trainings/explainable-ai/" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">full description</a> of the training on our website.Disclaimer:The appliedAI Institute for Europe gGmbH is supported by the KI-Stiftung Heilbronn gGmbH. The appliedAI Institute for Europe gGmbH is a subsidiary of the appliedAI Initiative GmbH.