DataRobot Blog

APRIL 29, 2022

This provides a great amount of benefit, but it also exposes institutions to greater risk and consequent exposure to operational losses. The stakes in managing model risk are at an all-time high, but luckily automated machine learning provides an effective way to reduce these risks.

Risk 111

Risk Modeling IT Risk Management 111

O'Reilly on Data

MAY 27, 2020

Under school district policy, each of Audrey’s eleven- and twelve-year old students is tested at least three times a year to determine his or her Lexile, a number between 200 and 1,700 that reflects how well the student can read. They test each student’s grasp of a particular sentence or paragraph—but not of a whole story.

Risk 355

Risk Testing Reporting Measurement 355

O'Reilly on Data

NOVEMBER 29, 2022

The financial collapse of 2008 led to tighter regulation of banks and financial institutions. Compared to cybersecurity risks, the scale of AI’s destructive power is potentially far greater. Even when catastrophes don’t kill large numbers of people, they often change how we think and behave. Good outcomes do not happen on their own.

Machine Learning 276

Machine Learning Recreation/Entertainment Risk Testing 276

Smart Data Collective

APRIL 13, 2021

Based on figures from Statista , the volume of data breaches increased from 2005 to 2008, then dropped in 2009 and rose again in 2010 until it dropped again in 2011. In 2009 for example, data breaches dropped to 498 million (from 656 million in 2008) but the number of records exposed increased sharply to 222.5 million in 2008).

Testing 122

Testing Behavioral Analytics Data-driven Big Data 122

O'Reilly on Data

JANUARY 25, 2021

in 2008 and continuing with Java 8 in 2014, programming languages have added higher-order functions (lambdas) and other “functional” features. Observability” risks becoming the new name for monitoring. It’s particularly difficult if testing includes issues like fairness and bias. Starting with Python 3.0 And that’s unfortunate.

Machine Learning 362

Machine Learning Software Testing Technology 362

O'Reilly on Data

JULY 15, 2019

In recent posts, we described requisite foundational technologies needed to sustain machine learning practices within organizations, and specialized tools for model development, model governance, and model operations/testing/monitoring. Note that the emphasis of SR 11-7 is on risk management.). Sources of model risk.

Machine Learning 37

Machine Learning Management Enterprise Risk Management 37

Domino Data Lab

AUGUST 8, 2019

2008 – Financial crisis : scientists flee Wall St. The probabilistic nature changes the risks and process required. Putting discussions about security aside, the statistics competency required to confront fairness and bias issues for machine learning models in production set quite a high bar. machine learning?

Data Science 71

Data Science Machine Learning Data Governance Statistics 71