Kediska Diiwaangelinta Model

Jawaabaha iyo sharraxaadaha waxay soo baxayaan markaad qaadanayso kediska.

1. Waa maxay ujeedada ugu weyn ee diiwaanka model?
   • Si loo calaamadiyo xogta tababarka cayriin
   • Si aad ugu adeegto sida buug-gacmeedka nooca gacanta lagu hayo iyo isha keliya ee runta ee moodooyinka la tababaray
   • Si aad u bedesho GPU-da server-ka
   • Si aad u qorto weydiimaha 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. Waa maxay nooca saxeexa ee diiwaanka?
   • Sawir-gacmeedka saynis yahanka xogta
   • Furaha sirta ah ee database-ka
   • Muddada tababarka ee moodeelka
   • Nidaam qeexaya qaabka la filayo iyo noocyada wax soo saarka
5. Waa maxay sababta nasabka la duubay (dataset, code commitment, hyperparameters) uu qiimo u leeyahay?
   • Waxay awood u siinaysaa dib-u-soo saaridda iyo hubinta sida nooc kasta loo dhisay
   • Waxay ka dhigaysa moodelku inuu si degdeg ah u socdo
   • Waxay si toos ah u kordhisaa saxnaanta moodeelka
   • Waxay ku cadaadinaysaa faylka qaabka
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