How to improve AI age identification accuracy?

I’m trying to crack my head around a key challenge at the moment. That is to increase
AI’s accuracy to be able to identify demographic age groups to plus minus 5 years
old.

Current AI settings only allow categorization of age groups of 20-24 years old,
25-29 years old…55 to 59 years old, 60 years old and above. Not plus minus.

I’m running a Data Management Platform (DMP) which collects demographic tag
information and these information are saved in Treasure Data.

I’m thinking of filtering groups of 10 years old , example 20-24, 25-29
as one group then feeding it to AI to try to increase accuracy instead of
inserting the full raw data CSV for AI to compute.

Do you think these are good ideas/methods? If yes, why. If no, any better
suggestions please?

The Data I have at the moment is not very large, average database of 100,000
users. I’m not able to increase this number any bigger at the moment.

Would be great if anyone could also advise or share on how best to
approach the challenges above and help shed some light on the challenges faced.

Many thanks in advance!
JM LeongAspiring Data AnalystAsked:
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Shaun VermaakTechnical SpecialistCommented:
Same as your other question; I believe it is far better to have historical data that includes those behaviours (whatever you have) in addition to the age. You can then use machine learning to guestimate the age.
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