O'Reilly on Data

DECEMBER 12, 2019

If a model is going to be used on all kinds of people, it’s best to ensure the training data has a representative distribution of all kinds of people as well. Interpretable ML models and explainable ML. The debugging techniques we propose should work on almost any kind of ML-based predictive model.

Machine Learning 198

Machine Learning Modeling Testing Risk Management 198

O'Reilly on Data

MARCH 20, 2019

The objective here is to brainstorm on potential security vulnerabilities and defenses in the context of popular, traditional predictive modeling systems, such as linear and tree-based models trained on static data sets. Applying data integrity constraints on live, incoming data streams could have the same benefits.

Modeling 227

Modeling Machine Learning Predictive Modeling Consulting 227

Cloudera

SEPTEMBER 7, 2023

Perhaps the biggest challenge of all is that AI solutions—with their complex, opaque models, and their appetite for large, diverse, high-quality datasets—tend to complicate the oversight, management, and assurance processes integral to data management and governance. Train and upskill employees.

Insurance 83

Insurance Risk Data-driven Finance 83

AWS Big Data

JANUARY 25, 2023

An AWS Glue crawler populates the AWS Glue Data Catalog with the data schema definitions (in a landing folder). AWS Glue is a serverless data integration service that makes it easier to discover, prepare, move, and integrate data from multiple sources for analytics, ML, and application development.

Visualization 76

Visualization Interactive Modeling Machine Learning 76