The Architecture Used at LinkedIn to Improve Feature Management in Machine Learning Models

The new typed feature schema streamlined the reusability of features across thousands of machine learning models.

The First Version

Typed Features

// Feature definition:
historicalActionsInFeed: {
doc: "Historical interactions on feed for members. go/linkToDocumentation"
version: "1.0"
dims: [
feedActions-1-0,
numberOfDays-1-0
]
valType: INT
availability: ONLINE
}
//////////
// Dimension definitions:
feedActions: {
doc: "The actions a user can take on main feed"
version: "1.0"
type: categorical : {
idMappingFile: "feedActions.csv"
}
}
numberOfDays: {
doc: "Count of days for historical windowing"
type: discrete
}
//////////
// Categorical definition (feedActions.csv):
0, OUT_OF_VOCAB
1, Comment
2, Click
3, Share

The Second Version

CEO of IntoTheBlock, Chief Scientist at Invector Labs, I write The Sequence Newsletter, Guest lecturer at Columbia University, Angel Investor, Author, Speaker.

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