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Explainable AI recipes : implement solutions to model explainability and interpretability with Python /
Understand how to use Explainable AI (XAI) libraries and build trust in AI and machine learning models. This book utilizes a problem-solution approach to explaining machine learning models and their algorithms. The book starts with model interpretation for supervised learning linear models, which in...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
[California] :
Apress,
[2023]
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
Tabla de Contenidos:
- Chapter 1: Introduction to Explainability Library Installations
- Chapter 2: Linear Supervised Model Explainability
- Chapter 3: Non-Linear Supervised Learning Model Explainability
- Chapter 4: Ensemble Model for Supervised Learning Explainability
- Chapter 5: Explainability for Natural Language Modeling
- Chapter 6: Time Series Model Explainability
- Chapter 7: Deep Neural Network Model Explainability.