towar
(pusty)
\nModel-agnostic methods for XAI are shown to produce explanations without relying on ML models internals that are \"opaque.\" Using examples from Computer Vision, the authors then look at explainable models for Deep Learning and prospective methods for the future.\n
przeczytaj całość
\n
Model-agnostic methods for XAI are shown to produce explanations without relying on ML models internals that are \"opaque.\" Using examples from Computer Vision, the authors then look at explainable models for Deep Learning and prospective methods for the future.
\n ukryj opis- Wydawnictwo: Springer Nature Switzerland AG
- Kod:
- Rok wydania: 2021
- Język: Angielski
- Oprawa: Miękka
- Liczba stron: 202
- Szerokość opakowania: 23.5 cm
- Wysokość opakowania: 15.5 cm
- Głębokość opakowania: 2.6 cm
- Waga: 336 g
Recenzja