Browse all content tagged with Metrics
The Logfire MCP Server connects AI assistants and LLMs to telemetry data via OpenTelemetry, enabling real-time querying, exception monitoring, root cause analysis, and custom SQL over your distributed traces and metrics using FlowHunt.
The Honeycomb MCP Server bridges AI assistants and Honeycomb observability data, enabling LLMs to securely analyze metrics, dashboards, and code behavior for enterprise workflows. It automates data analysis, accelerates root cause investigation, and streamlines SLO management within developer operations.
A confusion matrix is a machine learning tool for evaluating the performance of classification models, detailing true/false positives and negatives to provide insights beyond accuracy, especially useful in imbalanced datasets.
Fréchet Inception Distance (FID) is a metric used to evaluate the quality of images produced by generative models, particularly GANs. FID compares the distribution of generated images to real images, providing a more holistic measure of image quality and diversity.
