Idanwo ti o sopọ mọ itọsọna · Alabọde Ipele

Awoṣe Registries adanwo

Apply model registry versions, signatures, and deployment references, including why alias changes need a verified serving workflow.

Jẹmọ itọsọna awọn ọnaAwọn iforukọsilẹ awoṣe
Ibeere 1 ti 8

Kini idi akọkọ ti iforukọsilẹ awoṣe?

Awotẹlẹ gbogbo ibeere8 ibeere

Awọn idahun ati awọn alaye han bi o ṣe n mu ibeere naa.

  1. Kini idi akọkọ ti iforukọsilẹ awoṣe?
    • Lati aami data ikẹkọ aise
    • Lati ṣiṣẹ bi katalogi iṣakoso ti ikede ati orisun kan ti otitọ fun awọn awoṣe ikẹkọ
    • Lati rọpo GPU ni olupin kan
    • Lati kọ awọn ibeere SQL
  2. In current MLflow registry workflows, what can provide a named reference to a model version?
    • A reassignable model alias
    • A universal mandatory four-stage lifecycle in every registry
    • The training GPU’s display resolution
    • A random tensor without a model version
  3. How can a registry support a model rollback?
    • By guaranteeing every server switches instantly
    • By deleting all previous versions
    • By retaining a previous artifact that the serving workflow can reload and validate
    • By changing the training labels automatically
  4. Kini ibuwọlu awoṣe ni iforukọsilẹ?
    • Afọwọkọ ọwọ onimọ ijinle sayensi data
    • Ọrọigbaniwọle kan fun ibi ipamọ data
    • Akoko ikẹkọ awoṣe
    • Eto kan ti n ṣapejuwe igbewọle ti a nireti ti awoṣe ati awọn iru iṣelọpọ
  5. Kini idi ti iran ti o gbasilẹ (dataset, koodu ṣẹ, hyperparameters) ṣe pataki?
    • O jeki reproducibility ati auditability ti bi kọọkan ti ikede ti a še
    • O mu ki awoṣe ṣiṣẹ ni kiakia
    • O mu ki awọn awoṣe ká išedede laifọwọyi
    • O compresses awọn awoṣe faili
  6. What connects a registered model decision to an actual application rollout?
    • A guarantee that registering a version deploys it everywhere
    • A required fax to the GPU vendor
    • A configured deployment workflow that loads and verifies the chosen artifact
    • A model signature alone with no serving system
  7. A champion alias is reassigned, but a long-running server still has the old artifact loaded. What should an operator verify?
    • Only that the alias has a new value
    • That all servers reload automatically in every integration
    • Only the number of files in the registry
    • The artifact and version actually serving requests
  8. A model signature expects numerical columns but a request sends strings. What can signature-aware validation help detect?
    • Whether the training labels are morally correct
    • An input schema or type mismatch
    • Every possible accuracy regression
    • A guarantee that all numerical inputs are in distribution