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Automating Model Risk Compliance: Model Validation

DataRobot Blog

When the FRB’s guidance was first introduced in 2011, modelers often employed traditional regression -based models for their business needs. Furthermore, through its interactive interface, the modeler is able to do multiple what-if analyses to see the impact of changing the prediction threshold on the corresponding model precision and recall.

Risk 52
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Deep Learning Illustrated: Building Natural Language Processing Models

Domino Data Lab

Many thanks to Addison-Wesley Professional for providing the permissions to excerpt “Natural Language Processing” from the book, Deep Learning Illustrated by Krohn , Beyleveld , and Bassens. The excerpt covers how to create word vectors and utilize them as an input into a deep learning model. Introduction.

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Understanding the different types and kinds of Artificial Intelligence

IBM Big Data Hub

Early iterations of the AI applications we interact with most today were built on traditional machine learning models. These models rely on learning algorithms that are developed and maintained by data scientists. For example, Apple made Siri a feature of its iOS in 2011.

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Becoming a machine learning company means investing in foundational technologies

O'Reilly on Data

Consider deep learning, a specific form of machine learning that resurfaced in 2011/2012 due to record-setting models in speech and computer vision. A typical data pipeline for machine learning. If anything, deep learning models are even more data hungry than previous algorithms favored by data scientists.

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Data Science at The New York Times

Domino Data Lab

Here is a picture of The New York Times on its birthday in 1851, and for the vast majority of its lifespan this is pretty much what the user experience of interacting with The New York Times looks like. Editors can interact with this bot. Nobody paid any attention to it whatsoever until 2011. We crowdsourced it.