Domino Data Lab

MARCH 11, 2021

Machine learning (ML) frameworks are interfaces that allow data scientists and developers to build and deploy machine learning models faster and easier. What is your preferred programming language for artificial intelligence (AI) model development? How to choose the right ML Framework. Parameter Optimization.

Machine Learning 143

Machine Learning Deep Learning Insurance Modeling 143

Domino Data Lab

OCTOBER 1, 2020

Domino and Okera – Provide data scientists access to trusted datasets within reproducible and instantly provisioned computational environments. Domino Data Lab, the world’s leading data science platform, allows data scientists easy access to reproducible and easily provisioned computational environments.

Enterprise 105

Enterprise Metadata Cost-Benefit Data Science 105

CIO Business Intelligence

JULY 30, 2024

Many of the AI use cases entrenched in business today use older, more established forms of AI, such as machine learning, or don’t take advantage of the “generative” capabilities of AI to generate text, pictures, and other data. For many enterprises the return on investment for gen AI is elusive , he says.

Insurance 144

Insurance Machine Learning Interactive Finance 144

Domino Data Lab

AUGUST 6, 2021

Model Risk Management is about reducing bad consequences of decisions caused by trusting incorrect or misused model outputs. An enterprise starts by using a framework to formalize its processes and procedures, which gets increasingly difficult as data science programs grow. What Is Model Risk?

Risk Management 64

Risk Management Risk Modeling Enterprise 64

Domino Data Lab

FEBRUARY 20, 2019

Eugene Mandel , Head of Product at Superconductive Health , recently dropped by Domino HQ to candidly discuss cross-team collaboration within data science. Eugene Mandel , Head of Product at Superconductive Health , recently dropped by Domino HQ to discuss cross-team collaboration within data science.

Data Science 76

Data Science Testing Software Uncertainty 76

Domino Data Lab

JULY 22, 2019

Paco Nathan presented, “Data Science, Past & Future” , at Rev. At Rev’s “ Data Science, Past & Future” , Paco Nathan covered contextual insight into some common impactful themes over the decades that also provided a “lens” help data scientists, researchers, and leaders consider the future.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

CIO Business Intelligence

APRIL 29, 2025

IT leaders know they must eventually deal with technical debt, but because addressing it doesnt always directly result in increased revenue or new capabilities, it can be difficult to get business management to take it seriously. Manual remediation would have been prohibitively resource-intensive. Adding clarity to obscure code.

Testing 120

Testing Metrics Predictive Modeling Data-driven 120