1
Q
- TOKeN → A GeeRATiVE AI CosiCapT used to
A
2
Q
Represent WarDs
A
suB-Wasss or
3
Q
CHARACTERS THAT A MODel PRocesses
A
4
Q
AS DIscRetE UNiTS OF Text
A
5
Q
- SAmoliNg BIAS → OCCURS WItere THe DATA
A
6
Q
Ied to TRAiN THe MoDel Does NoT
A
7
Q
Reftet THe DinesiTy of THe ReAL
A
8
Q
WORLD POPULATION
A
9
Q
- CONFIRMATION BIAS → SeleCTiOly SeAcCHiaRy
A
10
Q
FOR OR INTERPRETINY INFORMATION TO
A
11
Q
CONFIRM ExiSTiNg BelieFs
A
12
Q
- ObSeRveR BiAS → HUMAN ERRORS OR
A
13
Q
SUBJecTiviTy DURiNg DATA AHALySiS OR
A
14
Q
ObseRvATion
A
15
Q
- MeASuReMenT BiAS → INACCURACIES IA DATA CollecTio
A
16
Q
- HAllUCINATION → THe MEE MODel GeNeRATES SCeMINGLy
A
17
Q
ACCURATE INFORMATION THAT IS INCORRECT
A
18
Q
OR FABRICATed
A
19
Q
- NegATIve PROMPTiNg → GuiDiNg A Gen AI MoDel to
A
20
Q
AVOiD CeRTAiN output oR BertAriRs
A
21
Q
шонн бенокАт ing Teyt
A
AWS AI Certified Practitioner Study Notes
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Decks in class (6)
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