Explainable AI for Practitioners designing and implementing explainable ML solutions

Most intermediate-level machine learning books focus on how to optimize models by increasing accuracy or decreasing prediction error. But this approach often overlooks the importance of understanding why and how your ML model makes the predictions that it does. Explainability methods provide an esse...

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Detalles Bibliográficos
Autor principal: Munn, Michael (ML solutions engineer) (-)
Otros Autores: Pitman, David, Taly, Ankur
Formato: Libro electrónico
Idioma:Inglés
Publicado: Sebastapol, CA : O'Reilly Media 2022.
Materias:
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009701321206719

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