Generative artificial intelligence explainable (2 Ergebnisse)

Hardcover. Zustand: new. Hardcover. This book integrates the concepts of explainable artificial intelligence and generative explainable artificial intelligence, showcasing how explainability can be incorporated into generative models. It highlights the importance of making generative models transparent, offering strategies to achieve this through interpretability techniques.The book:Focuses on the principles and methodologies of explainable artificial intelligence, providing readers with a thorough understanding of how artificial intelligence models can be made transparent and interpretable.Explores explainable artificial intelligence techniques, including feature importance, SHAP values, LIME, and counterfactual explanations.Offers an in-depth examination of generative artificial intelligence, covering cutting-edge advancements in generative models like GANs, VAEs, and transformer-based architectures.Bridges the gap between theoretical concepts and their practical applications, making advanced artificial intelligence technologies accessible to the readers.Includes numerous case studies and real-world examples that demonstrate the successful application of generative artificial intelligence and explainable artificial intelligence.The text is primarily written for graduate students and academic researchers in electrical engineering, electronics and communication engineering, computer science and engineering, biomedical engineering, and information technology. The text focuses on the methodologies of generative artificial intelligence, and explainable artificial intelligence, providing readers with an understanding of how artificial intelligence models can be transparent and interpretable. It explores various XAI techniques, feature importance, SHAP values, LIME, and counterfactual explanations. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Hardcover. Zustand: new. Hardcover. This book integrates the concepts of explainable artificial intelligence and generative explainable artificial intelligence, showcasing how explainability can be incorporated into generative models. It highlights the importance of making generative models transparent, offering strategies to achieve this through interpretability techniques.The book:Focuses on the principles and methodologies of explainable artificial intelligence, providing readers with a thorough understanding of how artificial intelligence models can be made transparent and interpretable.Explores explainable artificial intelligence techniques, including feature importance, SHAP values, LIME, and counterfactual explanations.Offers an in-depth examination of generative artificial intelligence, covering cutting-edge advancements in generative models like GANs, VAEs, and transformer-based architectures.Bridges the gap between theoretical concepts and their practical applications, making advanced artificial intelligence technologies accessible to the readers.Includes numerous case studies and real-world examples that demonstrate the successful application of generative artificial intelligence and explainable artificial intelligence.The text is primarily written for graduate students and academic researchers in electrical engineering, electronics and communication engineering, computer science and engineering, biomedical engineering, and information technology. The text focuses on the methodologies of generative artificial intelligence, and explainable artificial intelligence, providing readers with an understanding of how artificial intelligence models can be transparent and interpretable. It explores various XAI techniques, feature importance, SHAP values, LIME, and counterfactual explanations. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…