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# System prepended metadata

title: 2021 06 22 ML Solutions Meeting

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# 2021 06 22 ML Solutions Meeting

## Attendees
- Quansight
    - Kim
    - Fatma
    - Eric
    - Eskild
- Datum
    - Brian
    - Jeremy
    - Matthew

## Clients Needs
- Voter registration 
    - Using datum's data alongside client's data to decern which party the user is more associated with
    - Create lookalike audiences
        - Use known voters address --> device IDs
- Beeswax data
    - Row data with device ID with bid data 
    - Auction for ad placement
        - Bid logs and win logs
- 16 million Texas voter data
    - Perhaps start on a smaller scale - Austin area? 
    - If model is to be used statewide, use statewide data sampling
        - To avoid sampling bias
    - Stratification based on how democrat (DDD, DD, D)
        - Could we differentiate between the three groups?
- Classification models
    - XGBoost
        - Tree-based method
    - Multiclassification models 
    - Binary classification models would be simplier
    - Things to remember:
        - Data needs to be cleaned up
        - Requires labeled data
        - Use base URL and one-hot-encoding
        - Start simple!!
