Domino Data Lab

AUGUST 6, 2021

Model Risk Management is about reducing bad consequences of decisions caused by trusting incorrect or misused model outputs. Systematically enabling model development and production deployment at scale entails use of an Enterprise MLOps platform, which addresses the full lifecycle including Model Risk Management.

Risk Management 64

Risk Management Risk Modeling Enterprise 64

DataRobot Blog

MAY 26, 2022

In this post, we will dive deeper into how members from both the first and second line of defense within a financial institution can adapt their model validation strategies in the context of modern ML methods. In the model-fitting procedure, the modeler is then able to measure the impact of each factor against the outcome.

Risk 52

Risk Modeling Metrics Business Objectives 52

Domino Data Lab

APRIL 3, 2019

Also, while surveying the literature two key drivers stood out: Risk management is the thin-edge-of-the-wedge ?for Given those two, plus SQL gaining eminence as a database strategy, a decidedly relational picture coalesced throughout the decade. Andrew Ng later described this strategy as the “Virtuous Cycle of AI” – a.k.a.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

datapine

AUGUST 29, 2022

He founded the project Apache Storm in 2011, which turned to be “one of the world’s most popular stream processors and has been adopted by many of the world’s largest companies, including Yahoo!, Microsoft, Alibaba, Taobao, WebMD, Spotify, Yelp” according to Marz himself. Stein Kretsinger, founding executive, Advertising.

Big Data 263

Big Data Data Analytics Analytics Data mining 263