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...
| Otros Autores: | |
|---|---|
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
New York, NY :
Apress Media LLC
[2023]
|
| Edición: | 1st ed. 2023. |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009720737806719 |
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.
