Applied machine learning explainability techniques make ML models explainable and trustworthy for practical applications using LIME, SHAP, and more

Leverage top XAI frameworks to explain your machine learning models with ease and discover best practices and guidelines to build scalable explainable ML systems Key Features Explore various explainability methods for designing robust and scalable explainable ML systems Use XAI frameworks such as LI...

Ausführliche Beschreibung

Bibliographische Detailangaben

1. Verfasser:	Bhattacharya, Aditya (VerfasserIn)
Format:	Elektronisch E-Book
Sprache:	English
Veröffentlicht:	Birmingham Packt Publishing, Limited [2022]
Schlagworte:	Machine learning Apprentissage automatique
Online-Zugang:	lizenzpflichtig
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!