IBM Big Data Hub

OCTOBER 16, 2023

As more businesses use AI systems and the technology continues to mature and change, improper use could expose a company to significant financial, operational, regulatory and reputational risks. It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits.

Risk 72

Risk Modeling Management Metadata 72

DataKitchen

SEPTEMBER 21, 2023

This proactive approach to data quality guarantees that downstream analytics and business decisions are based on reliable, high-quality data, thereby mitigating the risks associated with poor data quality. ” For example, these tools may offer metadata-based notifications. What is Data in Use?

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

O'Reilly on Data

MARCH 20, 2019

Apply fair and private models, white-hat and forensic model debugging, and common sense to protect machine learning models from malicious actors. Like many others, I’ve known for some time that machine learning models themselves could pose security risks. they can train their own surrogate model.

Modeling 219

Modeling Machine Learning Predictive Modeling Consulting 219

Cloudera

MAY 12, 2021

Please note that use cases could include but are not limited to: risk modeling, sentiment analysis, next best action recommendation, anomaly detection, natural language generation, and more. HYBRID & MULTI-CLOUD INNOVATION. Read more about last years Data Impact Award winners.

Digital Transformation 68

Digital Transformation Machine Learning Optimization Data Lake 68

Alation

APRIL 14, 2022

In today’s AI/ML-driven world of data analytics, explainability needs a repository just as much as those doing the explaining need access to metadata, EG, information about the data being used. They strove to ramp up skills in all manner of predictive modeling, machine learning, AI, or even deep learning.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

IBM Big Data Hub

FEBRUARY 14, 2024

The IBM team is even using generative AI to create synthetic data to build more robust and trustworthy AI models and to stand in for real-world data protected by privacy and copyright laws. Banks and other lenders can use ML classification algorithms and predictive models to suggest loan decisions.

Cost-Benefit 83

Cost-Benefit Insurance Unstructured Data Machine Learning 83

Domino Data Lab

JANUARY 21, 2021

Predictive modeling efforts rely on dataset profiles , whether consisting of summary statistics or descriptive charts. Results become the basis for understanding the solution space (or, ‘the realm of the possible’) for a given modeling task. There is a risk of injecting bias. imputation of missing values). And the result?

Statistics 106

Statistics Unstructured Data Data Science Visualization 106