Kedis ku xidhan hagaha · Adag Heerka
U Diyaargarowga Xogta ee Kediska Mashaariicda AI
Wuxuu tijaabiyaa shanta hubin ee u diyaarsanaanta xogta, oo ay ku jirto eexda xulashada, daadinta xogta, heshiiska calaamadaynta iyo xadka sharciga ah sida xaddidaadda ujeedada GDPR.
Su'aal 1 ee 8
The bank has repayment outcomes only for approved applicants. Which data readiness problem does this show?
Horudhac su'aal kasta8 su'aalo
Jawaabaha iyo sharraxaadaha waxay soo baxayaan markaad qaadanayso kediska.
- The bank has repayment outcomes only for approved applicants. Which data readiness problem does this show?
- Duplicate records
- Selection bias that makes the data unrepresentative
- A slow API
- Label disagreement between annotators
- What is data leakage in the context of model training?
- Data being stolen by attackers
- Storage costs rising over time
- Losing records during migration
- Features that contain information only available after the outcome being predicted
- Which GDPR principle limits reusing data collected for one purpose for an incompatible new purpose?
- Purpose limitation
- Right to data portability
- Accountability
- Storage limitation
- In Data Readiness for AI Projects: what does Cohen's kappa measure?
- The speed of a data pipeline
- The number of missing values
- Agreement between annotators, corrected for chance
- The cost of labeling per item
- Why does retrieval for a generative AI assistant need to respect existing access permissions?
- To make responses load faster
- So the assistant does not reveal documents a user is not allowed to see
- Because embeddings need permissions to be calculated
- To lower the number of documents stored
- Why should forecasting models usually be tested on data split by time rather than randomly?
- It mirrors real deployment and avoids training on future information
- Kala qaybsanaanta random waa sharci-darro
- Time splits need less data
- Random splits cannot be used with labels
- Which statement reflects a common misconception about data readiness?
- Readiness depends on the specific use case
- Quality only needs to be good enough for the task
- Legal rights to use data must be checked
- A large volume of data means an organization is ready for AI
- What does a 'datasheets for datasets' document record?
- The cost of each database server
- The model's accuracy on the test set
- A dataset's origin, composition, collection method and intended use
- The passwords for accessing the data