DataRobot Blog

MAY 26, 2022

To start with, SR 11-7 lays out the criticality of model validation in an effective model risk management practice: Model validation is the set of processes and activities intended to verify that models are performing as expected, in line with their design objectives and business uses.

Risk 52

Risk Modeling Metrics Business Objectives 52

CIO Business Intelligence

OCTOBER 13, 2023

Deep learning engineer Deep learning engineers are responsible for heading up the research, development, and maintenance of the algorithms that inform AI and machine learning systems, tools, and applications.

Deep Learning 142

Deep Learning Machine Learning Modeling Software 142

IBM Big Data Hub

DECEMBER 15, 2023

While open-source AI offers enticing possibilities, its free accessibility poses risks that organizations must navigate carefully. Enterprises may expose their stakeholders to risk when they use technologies that they didn’t build in-house. Morgan’s Athena uses Python-based open-source AI to innovate risk management.

Deep Learning 66

Deep Learning Experimentation Machine Learning Risk 66

CIO Business Intelligence

SEPTEMBER 7, 2022

Cropin Apps, as the name suggests, comprises applications that support global farming operations management, food safety measures, supply chain and “farm to fork” visibility, predictability and risk management, farmer enablement and engagement, advance seed R&D, production management, and multigenerational seed traceability.

B2B 80

B2B Contextual Data IoT Deep Learning 80

O'Reilly on Data

DECEMBER 12, 2019

1] This includes C-suite executives, front-line data scientists, and risk, legal, and compliance personnel. These recommendations are based on our experience, both as a data scientist and as a lawyer, focused on managing the risks of deploying ML. That’s where model debugging comes in. Sensitivity analysis.

Machine Learning 187

Machine Learning Modeling Testing Risk Management 187

Ontotext

FEBRUARY 26, 2024

The answers to these foundational questions help you uncover opportunities and detect risks. Further, RED’s underlying model can be visually extended and customized to complex extraction and classification tasks. Why do risk and opportunity events matter? RED answers key questions such as: “What happened?”, “Who was involved?”,

Data-driven 59

Data-driven Risk Modeling Risk Management 59

IBM Big Data Hub

MAY 17, 2024

But as businesses around the globe rapidly adopt the technology to augment processes from merchandising to order management, there is some risk. Experiential product information Al tools allow individuals to learn more about products through processes like visual search, taking a photograph of an item to learn more about it.

B2B 66

B2B Interactive Optimization Forecasting 66