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Explainable Artificial Intelligence: Metodi, modelli e pratiche per comprendere e valutare le decisioni dell'IA
Paperback
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ISBN13: 9798193676485
Publisher: Independently Published
Published: Aug 19 2026
Pages: 116
Weight: 0.47
Height: 0.24 Width: 7.00 Depth: 10.00
Language: Italian
Publisher: Independently Published
Published: Aug 19 2026
Pages: 116
Weight: 0.47
Height: 0.24 Width: 7.00 Depth: 10.00
Language: Italian
Perché un modello di Intelligenza Artificiale prende una determinata decisione? Un sistema può essere accurato e, allo stesso tempo, apprendere correlazioni fragili, sfruttare informazioni irrilevanti o produrre decisioni difficili da verificare. L'Explainable Artificial Intelligence nasce per rendere osservabili questi meccanismi e trasformare le predizioni dei modelli in oggetti di analisi, valutazione e controllo. Questo manuale presenta in modo progressivo e scientificamente rigoroso i principali metodi dell'Explainable AI, partendo dalle basi del Machine Learning interpretabile fino alle tecniche post-hoc e ai modelli basati sui concetti. Nel libro vengono affrontati:
- interpretability, explainability, fidelity e valutazione delle spiegazioni;
- alberi decisionali, regole, GAM, GA2M, EBM e Neural Additive Models;
- prototipi, ProtoPNet e apprendimento logico induttivo;
- approcci neuro-simbolici, Semantic Loss, Markov Logic Networks, ProbLog e DeepProbLog;
- LIME, PredDiff, SHAP e KernelSHAP;
- gradienti, SmoothGrad, Integrated Gradients, Grad-CAM e attention;
- ICE, Partial Dependence Plot e Permutation Feature Importance;
- Concept Bottleneck Models, Concept Embedding Models e concept interventions;
- fairness, robustezza, sanity checks, governance e quadro normativo europeo.
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