Guide-yakabatana mibvunzo · Pakati Nhanho

Edza Tracking Quiz

Covers run metadata, metrics, artifacts, dataset identity, environment capture, and what experiment records can support.

Nzira dzekutungamira dzinoenderanaExperiment Tracking
Mubvunzo 1 ye 8

Ndechipi chinangwa chekutanga chekuyedza kutsvaga mukudzidza kwemichina?

Tarisa mubvunzo wese8 mibvunzo

Mhinduro uye tsananguro zvinoonekwa paunenge uchitora bvunzo.

  1. Ndechipi chinangwa chekutanga chekuyedza kutsvaga mukudzidza kwemichina?
    • Kuita kuti kumhanya kudzokororwe uye kuenzaniswa nekurekodha mamiriro avo akazara
    • Kuita kuti mamodheru adzidzire nekukurumidza paGPU
    • Kuendesa otomatiki mamodhi kune kugadzira
    • Kumanikidza modhi maremu ekuchengetedza
  2. Ndeupi musanganiswa wakakosha pakuita kuti dzidziso imwechete inyatsoita kuberekana?
    • Chekupedzisira chechokwadi nhamba
    • Code vhezheni, dataset, uye hyperparameters
    • Iyo tembiricha yeGPU uye kumhanya kwe fan
    • Zita remusayendisiti wedata
  3. Ndechipi cheizvi chiri chishandiso chakakurumbira chekutsvaga?
    • Photoshop
    • Kubernetes
    • MLflow
    • PostgreSQL
  4. Mazhinji ma tracker ekuedza anowanzo tora sei metric panguva yekudzidziswa?
    • Nekukopa manhamba manhamba muspredishiti mushure
    • Nekutora zvidzitiro zveiyo terminal
    • Nekuverenga kodhi yemodhi
    • Kuburikidza nekutema API mafoni akaiswa mukati mekudzidzira loop inoyerera ichienda kubackend
  5. Ndekupi zvinhu zvakakura zvakaita sezviremera zvemodhi yakachengetwa zvinowanzochengetwa nehurongwa hwekuronda?
    • Mune chinhu/chigadzirwa chekuchengetedza, chine mareferensi akachengetwa muchitoro chemetadata
    • Mukati memetrics database row
    • MuGPU ndangariro zvachose
    • Hazvina kuchengetwa zvachose
  6. Kuronda kwekuedza kuri kuitika sei munguva yemhando dzemitauro mikuru?
    • Iri kusiiwa nekuti maLLM haadi kuteedzera
    • Ikozvino zvakare inotora vhezheni dzekukurumidza, maratidziro ekuongorora, uye zvemhando yakabuda
    • Inongoteedzera mutengo weGPU izvozvi
    • Iyo yakabatanidzwa zvachose muvhidhiyo editing software
  7. Why record a dataset version or content hash with an ML run?
    • To prove the model is unbiased
    • To guarantee identical GPU arithmetic
    • So the run can be linked to the exact data snapshot used
    • To replace the code version
  8. In MLflow Tracking, where are large model files typically stored relative to parameters and metrics?
    • Only inside the metric names
    • Always embedded in the database row for each parameter
    • They are not recorded by a tracking system
    • In an artifact store, while run metadata is kept in a backend store