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 143

Deep Learning Machine Learning Modeling Software 143

IBM Big Data Hub

DECEMBER 15, 2023

Morgan’s Athena uses Python-based open-source AI to innovate risk management. Similarly, online educational platforms like Coursera and edX use open-source AI to personalize learning experiences, tailor content recommendations and automate grading systems.

Deep Learning 71

Deep Learning Experimentation Machine Learning Risk 71

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 85

B2B Contextual Data IoT Deep Learning 85

O'Reilly on Data

DECEMBER 12, 2019

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.

Machine Learning 191

Machine Learning Modeling Testing Risk Management 191

IBM Big Data Hub

AUGUST 28, 2023

Machine learning algorithms like Naïve Bayes and support vector machines (SVM), and deep learning models like convolutional neural networks (CNN) are frequently used for text classification. Crisis management and risk management: Text mining serves as an invaluable tool for identifying potential crises and managing risks.

Data mining 57

Data mining Machine Learning Deep Learning Marketing 57

IBM Big Data Hub

MAY 17, 2024

Poorly run implementations of traditional or generative AI technology in commerce—such as deploying deep learning models trained on inadequate or inappropriate data—lead to bad experiences that alienate both consumers and businesses. The technology can also provide strategic and personalized financial solutions.

B2B 58

B2B Interactive Optimization Forecasting 58

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. Conclusion.

Risk 52

Risk Modeling Metrics Business Objectives 52