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
기계 지원 번역 초안 (Korean) 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.
“예문 초안: 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.”
기계 지원 번역 초안 (Korean) for "Artifact Config Drift Check": Artifact Config Drift Check is a devops consistency check that finds differences between intended and live configuration for build output and package delivery. It uses desired state, live state, and diff reports so teams can avoid surprise environment behavior while keeping evidence, reliability, and public-safe operational boundaries clear.
“예문 초안: The DevOps team used Artifact Config Drift Check when the container image was signed, so the team could avoid surprise environment behavior before the deployment window opened.”
기계 지원 번역 초안 (Korean) for "Rollback Approval Step": Rollback Approval Step is a devops workflow control that requires review before a sensitive change proceeds for recovery from a bad deployment. It uses role checks, comments, and audit logs so teams can keep high-risk automation accountable while keeping evidence, reliability, and public-safe operational boundaries clear.
“예문 초안: The DevOps team used Rollback Approval Step when the error budget started burning, so the team could keep high-risk automation accountable before the deployment window opened.”
기계 지원 번역 초안 (Korean) for "Rollback Artifact Signature": Rollback Artifact Signature is a devops supply-chain record that proves that an artifact came from an expected build path for recovery from a bad deployment. It uses cryptographic signatures, provenance, and verification so teams can trust deployed packages while keeping evidence, reliability, and public-safe operational boundaries clear.
“예문 초안: The DevOps team used Rollback Artifact Signature when the error budget started burning, so the team could trust deployed packages before the deployment window opened.”
기계 지원 번역 초안 (Korean) for "Fine-Tuning Hyperparameter Sweep": Fine-Tuning Hyperparameter Sweep is a ml optimization process that searches over model settings to improve a target metric for adaptation of a model to a domain. It uses bounded search spaces, trial tracking, and early stopping so teams can find better configurations while keeping evidence, reliability, and public-safe operational boundaries clear.
“예문 초안: The machine learning team used Fine-Tuning Hyperparameter Sweep when the fine-tuning run used curated examples, so the team could find better configurations before the model moved into evaluation.”
기계 지원 번역 초안 (Korean) for "Environment Build Gate": Environment Build Gate is a devops quality gate that blocks promotion when required checks fail for configuration for a runtime stage. 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.
“예문 초안: The DevOps team used Environment Build Gate when staging and production drifted, so the team could prevent broken releases before the deployment window opened.”
기계 지원 번역 초안 (Korean) for "Metric Data Split": Metric Data Split is a ml experimental control that separates examples for training, validation, and testing for measurement of model behavior. It uses randomization rules, leakage checks, and seed tracking so teams can measure generalization honestly while keeping evidence, reliability, and public-safe operational boundaries clear.
“예문 초안: The machine learning team used Metric Data Split when the metric changed after data cleanup, so the team could measure generalization honestly before the model moved into evaluation.”
기계 지원 번역 초안 (Korean) for "CI Release Manifest": CI Release Manifest is a devops delivery record that lists versions, artifacts, routes, and checks for a release for continuous integration workflows. It uses commit IDs, checksums, and deployment URLs so teams can make releases auditable while keeping evidence, reliability, and public-safe operational boundaries clear.
“예문 초안: The DevOps team used CI Release Manifest when a pull request entered the build queue, so the team could make releases auditable before the deployment window opened.”
기계 지원 번역 초안 (Korean) for "CI Infra Plan": CI Infra Plan is a devops change preview that shows expected infrastructure changes before apply for continuous integration workflows. It uses resource graphs, policy checks, and cost notes so teams can review platform changes safely while keeping evidence, reliability, and public-safe operational boundaries clear.
“예문 초안: The DevOps team used CI Infra Plan when a pull request entered the build queue, so the team could review platform changes safely before the deployment window opened.”
기계 지원 번역 초안 (Korean) for "Fine-Tuning Provenance Ledger": Fine-Tuning Provenance Ledger is a ml record that tracks where data came from and how it changed for adaptation of a model to a domain. It uses hashes, source labels, and transformation history so teams can audit model inputs reliably while keeping evidence, reliability, and public-safe operational boundaries clear.
“예문 초안: The machine learning team used Fine-Tuning Provenance Ledger when the fine-tuning run used curated examples, so the team could audit model inputs reliably before the model moved into evaluation.”