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
機械支援の翻訳下書き (Japanese) 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.
“例文の下書き: 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.”
機械支援の翻訳下書き (Japanese) for "Artifact Secret Rotation": Artifact Secret Rotation is a devops credential workflow that replaces sensitive keys without service interruption for build output and package delivery. It uses dual credentials, rollout steps, and revocation so teams can reduce credential exposure while keeping evidence, reliability, and public-safe operational boundaries clear.
“例文の下書き: The DevOps team used Artifact Secret Rotation when the container image was signed, so the team could reduce credential exposure before the deployment window opened.”
機械支援の翻訳下書き (Japanese) 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.
“例文の下書き: 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.”
機械支援の翻訳下書き (Japanese) for "Artifact Release Manifest": Artifact Release Manifest is a devops delivery record that lists versions, artifacts, routes, and checks for a release for build output and package delivery. It uses commit IDs, checksums, and deployment URLs so teams can make releases auditable while keeping evidence, reliability, and public-safe operational boundaries clear.
“例文の下書き: The DevOps team used Artifact Release Manifest when the container image was signed, so the team could make releases auditable before the deployment window opened.”
機械支援の翻訳下書き (Japanese) for "Artifact Incident Timeline": Artifact Incident Timeline is a devops response record that orders alerts, actions, and decisions during an incident for build output and package delivery. It uses timestamps, owners, and evidence links so teams can learn from outages without guesswork while keeping evidence, reliability, and public-safe operational boundaries clear.
“例文の下書き: The DevOps team used Artifact Incident Timeline when the container image was signed, so the team could learn from outages without guesswork before the deployment window opened.”
機械支援の翻訳下書き (Japanese) for "CD Rollout Guard": CD Rollout Guard is a devops release control that limits exposure during gradual deployment for deployment automation and promotion. It uses traffic slices, health checks, and automatic pause rules so teams can reduce blast radius while keeping evidence, reliability, and public-safe operational boundaries clear.
“例文の下書き: The DevOps team used CD Rollout Guard when the release moved toward production, so the team could reduce blast radius before the deployment window opened.”
機械支援の翻訳下書き (Japanese) for "Pipeline Provenance Ledger": Pipeline Provenance Ledger is a ml record that tracks where data came from and how it changed for automated data and model workflow. 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.
“例文の下書き: The machine learning team used Pipeline Provenance Ledger when the pipeline missed a validation step, so the team could audit model inputs reliably before the model moved into evaluation.”
機械支援の翻訳下書き (Japanese) for "Artifact Artifact Signature": Artifact Artifact Signature is a devops supply-chain record that proves that an artifact came from an expected build path for build output and package delivery. It uses cryptographic signatures, provenance, and verification so teams can trust deployed packages while keeping evidence, reliability, and public-safe operational boundaries clear.
“例文の下書き: The DevOps team used Artifact Artifact Signature when the container image was signed, so the team could trust deployed packages before the deployment window opened.”
機械支援の翻訳下書き (Japanese) for "CI Incident Timeline": CI Incident Timeline is a devops response record that orders alerts, actions, and decisions during an incident for continuous integration workflows. It uses timestamps, owners, and evidence links so teams can learn from outages without guesswork while keeping evidence, reliability, and public-safe operational boundaries clear.
“例文の下書き: The DevOps team used CI Incident Timeline when a pull request entered the build queue, so the team could learn from outages without guesswork before the deployment window opened.”
機械支援の翻訳下書き (Japanese) 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.
“例文の下書き: 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.”