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artificial intelligence

A collection of 3 posts
Part II - Explainable ML Models: Local post hoc explanations
xai

Part II - Explainable ML Models: Local post hoc explanations

Post hoc explanations approximate the behavior of a black-box by extracting relationships between feature values and the predictions. Several local explanation methods are model-agnostic, meaning they do not have access to the internal structure of the model.
May 25, 2021 3 min read
Explainable ML Models: what are explanations and why do we need them? – Part I
xai

Explainable ML Models: what are explanations and why do we need them? – Part I

Interpretability is a key element of trust for AI models. An explanation is an interpretable description of a model behavior. For an explanation to be valid it needs to be faithful to the model and it needs to be understandable to the user.
May 22, 2021 3 min read
Redefining the Newsletter Experience
artificial intelligence

Redefining the Newsletter Experience

A decline in trust in media and the need to access unbiased information, are two of the many reasons why a wave of local, reader-supported newspapers is emerging. Local news publishers build a closer tie with the readers by talking about the community, city development, and the local government they
Apr 1, 2021 3 min read
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