quiz bu lëkkale ak tegtal · Diggante Niveau

IA ci Quiz Sistemu Tegtal

Xoolaat segg bi lalu ci lëkkaloo ak ëmbiit li, done yu bari yu jëfandikukat yi, àppu ndoorte lu sedd, ak jagleel ngir jàngat xalaat yiñ tànn.

Yooni njiit yu jëm ciIA ci sistemu xalaat
Laaj 1 de 8

Lan mooy segg lëkkaloo?

Xoolaatal laaj bu nekk8 laaj

Sooy def quiz bi, tontu yi ak leeral yi dañuy feeñ.

  1. Lan mooy segg lëkkaloo?
    • Modèlu tànneef ci jëfandikukat yu bari
    • Kulòor yi ñuy jëfandikoo ci nataalu benn mbir
    • Guddaayi fi ñuy leeral produit yi
    • jaxase katalog bi ci anam wu mujjee
  2. Lan la segg ëmbiit li di jëfandikoo ngir joxe xalaat?
    • Waxtu bis bi kese
    • Man-mani mbir yi ak say tànneef yu njëkk
    • Njëg bu aksioŋ yi ci liggéeyukaay bi
    • Flip xaalis
  3. Ban jafe-jafe la faktorisasioŋ matriks di saafara ci ñiy xelal nit ñi?
    • Encrypter baatu-jàll jëfandikukat
    • Komprime fichier wideo
    • Soppi ab matrix jëfandikukat bu bari ay vecteur yu nëbbu
    • Route dem bi ak dikk bi ci internet
  4. Luy jafe-jafe 'tàmbali bu sedd'?
    • Serveur yi dañu sedd lool ngir mëna dox
    • Virus buy congeler ay kontu
    • Liñu lay digal nga liggéey ci hiver bi kese
    • Jafe-jafe bi ñuy xelal jëfandikukat yu bees yi wala mbir yu amul jaar-jaar
  5. Ban competition moo jàppale ñu siiwal gëstub recommandation?
    • Neexal bu Netflix bi
    • Neexal bu Turing
    • Prix Nobel bi
    • Eurovision
  6. What did Meyer and colleagues propose the Average Measure of Impact to evaluate?
    • Image classification accuracy
    • The impact of personalized recommendations on usefulness and trust
    • The number of ratings stored in a matrix
    • The GPU memory used by a recommender
  7. Which metric is designed to assess the quality of a ranked top-K recommendation list?
    • Mean absolute error on a single rating only
    • Pixel yu jaar yoon
    • NDCG@K
    • Tolluwaayu njuumte ci baat
  8. Why can a low rating-prediction error fail to guarantee a good recommendation list?
    • RMSE directly measures user satisfaction for every ranking
    • Every user sees every catalog item
    • A rating model cannot use user-item data
    • Rating accuracy and top-item ranking quality are different objectives