Feature Dukaamada Kediska

Jawaabaha iyo sharraxaadaha waxay soo baxayaan markaad qaadanayso kediska.

1. Why use shared feature definitions for training and online serving?
   • To guarantee every cached value is always fresh
   • To reduce skew caused by separate transformation implementations
   • To eliminate the need for timestamps
   • To choose a GPU model automatically
2. Waa maxay farqiga u dhexeeya dukaamada offline iyo online?
   • Qad la'aanta waxay haysaa xogta taariikhiga ah ee tababarka; online waxay si degdeg ah ugu adeegtaa qiyamkii ugu dambeeyay saadaasha tooska ah
   • Qad la'aanta waxaa loogu talagalay sawirrada, onlayn waa qoraal
   • Waa isku mid oo leh magacyo kala duwan
   • Khadka tooska ah wuxuu shaqeeyaa maalmaha fasaxa ah, onlaynku wuxuu shaqeeyaa maalmaha shaqada
3. Waa maxay sababta ku biirista wakhtiga-dhibcaha ay muhiim u yihiin marka la dhisayo xogta tababarka?
   • Waxay ka dhigaan kaydka xogta inuu si degdeg ah u shaqeeyo
   • Waxay u tarjumaan sifooyinka luqado kale
   • Waxay ka hortagaan daadinta xogta iyagoo isticmaalaya qiyamka sifada sidii ay ahaayeen wakhti dhacdo kasta
   • Waxay yareeyaan cabbirka faylka qaabka
4. Which storage pattern commonly supports low-latency feature lookup by entity key?
   • An archival tape read for every request
   • A printed document catalog
   • A model-weight-only file
   • A key-value online store such as Redis or DynamoDB
5. Waa maxay 'sifada' macnaha guud?
   • Doorsoome wax gal ah oo laga soo qaatay xogta, sida celceliska kharashka 30 maalmood
   • Cilad ku jirta koodka moodeelka
   • Habka midabka dashboard-ka
   • Nooc ka mid ah GPU-da
6. Waa maxay faa'iidada dheeraadka ah ee uu bixiyo buug-gacmeedka sifada la wadaago?
   • Waxay si toos ah u tirtirtaa xogtii hore saacad kasta
   • Waxay bedeshaa baahida loo qabo tababar nooc kasta ah
   • Waxay u ogolaataa sifooyin loo dhisay hal nooc in la ogaado oo dib loo isticmaalo moodooyinka kale
   • Waxay siraysaa iimaylka shirkadda
7. A feature’s event time precedes a loan decision, but the value only arrived afterward. What must a historical training join consider?
   • Only whether its column name is short
   • A rule that every past event was already known
   • Only the current online value
   • Whether that value was actually available at prediction time
8. An online feature has not been refreshed after new events arrived. Which property should a feature-store monitor inspect?
   • The font size of the registry page
   • Feature freshness relative to the prediction’s needs
   • The model’s number of attention heads only
   • Whether the feature name contains a digit