# ML Model Monitoring Resources Detect model drift, assess performance and integrity, and set alerts ## Resources - [AI Forward Summit](/content/topic/ai-forward/index.html) - [Generative AI and LLMOps](/content/topic/generative-ai-and-llmops/index.html) - [Use Cases](/content/topic/ai-use-cases/index.html) - [Responsible AI](/content/topic/responsible-ai/index.html) - [AI Observability](/content/topic/ai-observability/index.html) - [MLOps](/content/topic/mlops/index.html) - [Bias and Fairness](/content/topic/bias-and-fairness-in-ai/index.html) - [Explainable AI](/content/topic/explainable-ai/index.html) ## Video ### [Compare and Analyze Cohorts Using Segment Monitoring](/content/resources/compare-and-analyze-cohorts-using-segment-monitoring/index.html) In this product tour, see how to configure Fiddler’s dashboards for specific teams, business goals, and use cases. ### [Get Rich Insights on LLM Applications and ML Models with Customizable Dashboards](/content/resources/get-rich-insights-with-customizable-dashboards/index.html) In this product tour, see how to configure Fiddler’s dashboards for specific teams, business goals, and use cases. ### [Track Model Drift on Unstructured Data](/content/resources/track-model-drift-on-unstructured-data/index.html) In this product tour, we walk through tracking drift for models like image classifiers by leveraging image embeddings and text embeddings. ### [Measuring Distributional Shifts in Text: The Advantage of Language Model-Based Embeddings](/content/resources/measuring-distributional-shifts-in-text-the-advantage-of-language-model-based-embeddings/index.html) Explore a method for measuring distributional shifts in text data using language model-based embeddings, highlighting the effectiveness of LLMs in capturing semantic relationships for this purpose. ### [Quicktour: Monitor NLP and LLM-based Embeddings for Data Drift](/content/resources/monitor-nlp-and-llm-based-embeddings-for-data-drift/index.html) Learn how Fiddler’s unique, clustering-based method accurately monitors data drift in NLP models and LLM-based embeddings. ### [LLM-based Embedding Monitoring: Track LLM Performance by Monitoring Drift](/content/resources/llm-based-embedding-monitoring-track-llm-performance-by-monitoring-drift/index.html) Learn how to track the performance of LLM-based embeddings from OpenAI, Cohere, Anthropic, and other LLMs by monitoring drift using Fiddler. ### [Custom Dashboards and Insights: Increase Organizational Alignment for Better Decision Making](/content/resources/custom-dashboards-and-insights-increase-organizational-alignment-for-better-decision-making/index.html) Learn how Fiddler’s custom dashboards help ML teams obtain actionable model insights, and increase organizational alignment and collaboration. ### [Monitor Model Performance and Drift](/content/resources/monitor-model-performance-and-drift/index.html) Learn how to quickly detect model performance and drift issues, and reduce the time to troubleshoot issues with root cause analysis using Fiddler. ### [Monitoring Models with Unstructured Data](/content/resources/monitoring-models-with-unstructured-data/index.html) Learn how to monitor models with unstructured data using Fiddler's cluster-based binning approach. ### [A Human-Centric Take on Model Monitoring](/content/resources/a-human-centric-take-on-model-monitoring/index.html) Learn the human-centric challenges and requirements for ML model monitoring in real-world applications. ### [AI Explained: Unraveling Unstructured Text and Image Models](/content/webinars/ai-explained-unraveling-unstructured-text-and-image-models/index.html) Watch this on-demand webinar with Josh Rubin, Director of Data Science at Fiddler AI, to understand how to improve unstructured model performance. ### [The New Fiddler for Unstructured Models and Advanced XAI](/content/webinars/the-new-fiddler-for-unstructured-models-and-advanced-xai/index.html) Watch this demo-driven webinar to learn the major updates to the Fiddler MPM platform. ### [AI Explained: Rethinking Model Monitoring](/content/webinars/ai-explained-rethinking-model-monitoring/index.html) Watch this on-demand AI Explained with Shreya Shankar, PhD Student at UC Berkeley, to learn the mess plaguing ML workflows, emerging research around model monitoring, and how to build responsible AI. ### [AI Explained: Model Monitoring Best Practices IRL](/content/webinars/ai-explained-model-monitoring-best-practices-irl/index.html) Watch this on-demand webinar with Hima Lakkaraju, Assistant Professor at Harvard University, to learn model monitoring best practices, why an organization should have it, and how to integrate it into MLOps workflows. ## Guides - [The Ultimate Guide to Large Language Model (LLM) Monitoring](/content/guides/the-ultimate-guide-to-llm-monitoring/index.html) Learn how enterprises use large language model (LLM) Monitoring using a comprehensive AI Observability platform to ensure high performance, behavior, and safety of LLM Applications. - [The Rise of MLOps Monitoring](/content/guides/the-rise-of-mlops-monitoring/index.html) Read about the rise of MLOps monitoring and how it helps IT teams accelerate the life cycle of development. Prepare for a successful AI deployment today. - [Model Monitoring Best Practices](/content/guides/ml-model-monitoring-best-practices/index.html) Download the whitepaper to learn best practices for model monitoring, model monitoring tools and techniques, and the role of explainability. - [Class Imbalance: Monitoring Rare and Nuanced Model Drift](/content/guides/class-imbalance-monitoring-rare-and-nuanced-model-drift/index.html) Download the whitepaper to learn what class imbalance is, how to detect drift, the impact on ML models, and how to address it for effective model monitoring. - [How to Measure ML Model Drift](/content/guides/how-to-measure-ml-model-drift/index.html) Download the whitepaper to learn why model drift is important, how to measure model drift, and more. - [Model Performance Management Best Practices](/content/guides/optimizing-mlops-with-ml-mpm-powered-by-explainable-ai/index.html) Learn the unique nature of machine learning, its challenges, and how to create a disciplined model performance management framework. - [The Ultimate Guide to Model Performance](/content/guides/the-ultimate-guide-to-ml-model-performance/index.html) ML models naturally degrade in performance over time. To catch and correct performance issues, teams must monitor model performance throughout the ML lifecycle. ## Articles - [Agentic Framework in AI: A Comprehensive Analysis](/content/articles/agentic-framework-analysis-autonomous-development/index.html) Explore the agentic framework in AI, its differences from other frameworks, and its applications in autonomous development. - [Agentic AI in Healthcare: Driving Smarter Clinical Decisions and Patient Engagement](/content/articles/agentic-ai-in-healthcare/index.html) Explore how agentic AI is transforming healthcare by enabling smarter clinical decisions and improving patient engagement. - [Agentic AIOps: The Evolution of AI Agents for Next-Gen Operations with Agentic AI Platforms](/content/articles/agentic-aiops/index.html) Discover how Fiddler Agentic AIOps transforms AI operations, enhancing decision-making and optimizing workflows for next-gen AI systems. - [Leveraging AI Guardrail Metrics to Strengthen LLM Reports](/content/articles/ai-guardrails-metrics/index.html) Explore how AI guardrails reports and LLM metrics enhance enterprise AI security, accountability, and performance with Fiddler Trust Service. - [Why AI Security is Critical for Enterprise Organizations](/content/articles/ai-security-for-enterprises/index.html) Learn why AI security is essential for enterprises and how platforms like Fiddler help protect models, data, and systems at scale. - [A Complete Guide to Machine Learning Model Lifecycle Management](/content/articles/machine-learning-model-lifecycle-management/index.html) Learn how to effectively manage the machine learning model lifecycle and discover how Fiddler streamlines model monitoring for enterprise success. - [Evaluating the ROI of AI Explainability Tools](/content/articles/evaluating-the-roi-of-ai-explainability-tools/index.html) Discover how Fiddler AI’s explainability improves ML performance, transparency, and trust. Gain clearer insights into ML model predictions and outcomes. - [Navigating AI Compliance and Risk Management](/content/articles/ai-compliance-and-risk-management/index.html) Discover how the Fiddler AI Observability and Security platform helps organizations manage LLM compliance and risks, ensuring safe and trustworthy LLM deployment at scale. - [Maximizing AI Guardrails Velocity: Fast, Secure Innovation at Scale](/content/articles/ai-guardrails-velocity/index.html) Discover how AI Guardrails accelerate innovation without sacrificing security. Learn how Fiddler enables fast, secure LLM deployment at scale. - [How to Avoid LLM Security Risks](/content/articles/how-to-avoid-llm-security-risks/index.html) Discover how to avoid LLM security risks with Fiddler AI. Our observability and guardrails tools detect risks and set alerts for quick jailbreak responses. - [AI Agent Monitoring: Key Steps and Methods to Ensure Performance and Reliability](/content/articles/ai-agent-evaluation/index.html) Learn how to evaluate AI agents with key steps and metrics using Fiddler to boost performance, ensure reliability, and support continuous improvement. - [Guide to Building RAG-Based LLM Applications for Production](/content/articles/rag-based-llm/index.html) Discover how to build RAG-based LLM applications for production with Fiddler, and learn how to safeguard, monitor, and optimize LLM performance. - [How to Leverage AI Predictive Analytics to Forecast Model Behavior](/content/articles/ai-predictive-analytics/index.html) Discover how AI predictive analytics helps forecast model behavior, optimize outcomes, and improve decision-making with Fiddler AI Observability. - [Managing Responsible Multi-Agent LLM Systems for Enterprise Applications](/content/articles/multi-agent-llm-systems-for-enterprises/index.html) Learn best practices, importance, and benefits of managing multi-agent LLM systems in enterprises. Discover how Fiddler can assist with seamless management. - [How to Build an AI Agent: A Step-by-Step Guide for Enterprises](/content/articles/building-ai-agents/index.html) Learn how to build AI agents with this step-by-step guide for enterprises—covering frameworks, benefits, use cases, and Fiddler’s AI monitoring support.