Define the new internet.
Look up the words people use online, add the ones we missed, and help make the internet easier to understand.
Look up the words people use online, add the ones we missed, and help make the internet easier to understand.
2,337 definitions
机器辅助翻译草稿 (Chinese) for "Environment Runbook Check": Environment Runbook Check is a devops operational test that confirms that documented procedures still work for configuration for a runtime stage. It uses dry runs, screenshots, and command validation so teams can keep response playbooks current while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The DevOps team used Environment Runbook Check when staging and production drifted, so the team could keep response playbooks current before the deployment window opened.”
机器辅助翻译草稿 (Chinese) for "Fine-Tuning Model Card": Fine-Tuning Model Card is a ml documentation artifact that summarizes intended use, limits, and evaluation evidence for adaptation of a model to a domain. It uses dataset notes, metric tables, and risk statements so teams can publish model behavior honestly while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The machine learning team used Fine-Tuning Model Card when the fine-tuning run used curated examples, so the team could publish model behavior honestly before the model moved into evaluation.”
机器辅助翻译草稿 (Chinese) for "Fine-Tuning Label Review": Fine-Tuning Label Review is a ml quality workflow that checks annotations for consistency and usefulness for adaptation of a model to a domain. It uses agreement metrics, reviewer queues, and adjudication so teams can improve supervised learning data while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The machine learning team used Fine-Tuning Label Review when the fine-tuning run used curated examples, so the team could improve supervised learning data before the model moved into evaluation.”
机器辅助翻译草稿 (Chinese) for "Metric Calibration Curve": Metric Calibration Curve is a ml diagnostic that compares predicted confidence with observed outcomes for measurement of model behavior. It uses bucketed predictions, reliability diagrams, and threshold analysis so teams can make confidence scores useful while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The machine learning team used Metric Calibration Curve when the metric changed after data cleanup, so the team could make confidence scores useful before the model moved into evaluation.”
机器辅助翻译草稿 (Chinese) for "CI Trace Link": CI Trace Link is a devops observability link that connects a deployment or workflow to runtime evidence for continuous integration workflows. It uses trace IDs, span metadata, and release identifiers so teams can debug production changes faster while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The DevOps team used CI Trace Link when a pull request entered the build queue, so the team could debug production changes faster before the deployment window opened.”
机器辅助翻译草稿 (Chinese) for "Environment Trace Link": Environment Trace Link is a devops observability link that connects a deployment or workflow to runtime evidence for configuration for a runtime stage. It uses trace IDs, span metadata, and release identifiers so teams can debug production changes faster while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The DevOps team used Environment Trace Link when staging and production drifted, so the team could debug production changes faster before the deployment window opened.”
机器辅助翻译草稿 (Chinese) for "Pipeline Model Card": Pipeline Model Card is a ml documentation artifact that summarizes intended use, limits, and evaluation evidence for automated data and model workflow. It uses dataset notes, metric tables, and risk statements so teams can publish model behavior honestly while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The machine learning team used Pipeline Model Card when the pipeline missed a validation step, so the team could publish model behavior honestly before the model moved into evaluation.”
机器辅助翻译草稿 (Chinese) for "Rollback Build Gate": Rollback Build Gate is a devops quality gate that blocks promotion when required checks fail for recovery from a bad deployment. It uses tests, lint, security scans, and policy rules so teams can prevent broken releases while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The DevOps team used Rollback Build Gate when the error budget started burning, so the team could prevent broken releases before the deployment window opened.”
机器辅助翻译草稿 (Chinese) for "CI Build Gate": CI Build Gate is a devops quality gate that blocks promotion when required checks fail for continuous integration workflows. It uses tests, lint, security scans, and policy rules so teams can prevent broken releases while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The DevOps team used CI Build Gate when a pull request entered the build queue, so the team could prevent broken releases before the deployment window opened.”
机器辅助翻译草稿 (Chinese) for "Metric Embedding Refresh": Metric Embedding Refresh is a ml index workflow that updates vector representations after source data changes for measurement of model behavior. It uses batch jobs, backfills, and index validation so teams can keep retrieval results current while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The machine learning team used Metric Embedding Refresh when the metric changed after data cleanup, so the team could keep retrieval results current before the model moved into evaluation.”