Discover how Fiddler AI Observability’s advanced image explainability helps you gain deep insights into the predictions and behaviors of computer vision models.
Watch this session with George Mathew, Managing Director at Insight Partners to learn about the current state of AI, the different modalities of human and machine interaction, the advancements, and challenges AI presents.
Learn how to perform root cause analysis to gain contextual insights, and improve model outcomes using Fiddler's analytics capabilities.
Learn how to get a deep understanding of model predictions using Fiddler's explainability capabilities.
Hima Lakkaraju, assistant professor at Harvard University, explains how to monitor the behavior of ML models through model interpretations and explanations.
Krishnaram Kenthapadi, Chief Scientist at Fiddler AI, explains the common model issues that lead to performance degradation and how to monitor ML models.
Learn about FairCanary, a novel approach to generating feature-level bias explanations that is an order of magnitude faster than previous methods.
A panel of industry and research experts discuss the state of explainable AI today and what the future holds.
Read about GroupShapley and GroupIG (Integrated Gradients), axiomatically justified methods to understand drift in ML model prediction distributions over time.
Improve your MLOps workflow on SageMaker using Fiddler's Model Performance Management platform.
Watch this panel discussion on building responsible, ethical, and accountable AI.
Learn how organizations view and use explainability for stakeholder consumption, including a framework for establishing clear goals for explainability.
Learn how subtle differences in the underlying game formulations of existing methods can cause large differences in the attributions for a prediction.
Learn how randomized feature ablation helps measure the importance of a feature on a model's ability to make good predictions.
An overview of model interpretability and explainability in AI, key regulations/laws, and techniques/tools for providing explainability as part of AI/ML systems
Watch this on-demand webinar to learn from Tirthajyoti Sarkar, Sr. Director, AI/ML Platform at Rhombus Power Inc, on the value of XAI for ML models, how to do XAI right, and why explainability is critical.
Watch this demo-driven webinar to learn the major updates to the Fiddler MPM platform.
Learn the unique nature of machine learning, its challenges, and how to create a disciplined model performance management framework.
Learn how to build ethical AI using explainable AI in these whitepapers. If you use artificial intelligence you need to ensure it's responsible and fair.
Download the brief to learn how explainable AI works in Fiddler, proprietary techniques used to explain model behavior, and Explainable AI use cases
With Fiddler, Conjura enjoys visibility into model events: predictions and changes, record of how models have been performing over time, single source of truth for model predictions, and more!
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