Remove 2019 Remove Data Processing Remove Deep Learning Remove Risk Management
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What a quarter century of digital transformation at PayPal looks like

CIO Business Intelligence

These applications live on innumerable servers, yet some technology is hosted in the public cloud. User data is also housed in this layer, including profile, behavior, transactions, and risk. We’ve been working on this for over a decade, including transformer-based deep learning,” says Shivananda.

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Why you should care about debugging machine learning models

O'Reilly on Data

In addition to newer innovations, the practice borrows from model risk management, traditional model diagnostics, and software testing. While our analysis of each method may appear technical, we believe that understanding the tools available, and how to use them, is critical for all risk management teams.

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Themes and Conferences per Pacoid, Episode 8

Domino Data Lab

Data governance shows up as the fourth-most-popular kind of solution that enterprise teams were adopting or evaluating during 2019. That’s a lot of priorities – especially when you group together closely related items such as data lineage and metadata management which rank nearby. Rinse, lather, repeat. a second priority?at