O'Reilly on Data

NOVEMBER 29, 2022

The financial collapse of 2008 led to tighter regulation of banks and financial institutions. An outcomes-based strategy would look at the impact of an AI or ML solution on specific categories and subgroups of stakeholders. Even when catastrophes don’t kill large numbers of people, they often change how we think and behave.

Machine Learning 282

Machine Learning Recreation/Entertainment Risk Testing 282

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 123

Testing Behavioral Analytics Data-driven Big Data 123

DataRobot Blog

APRIL 29, 2022

Prior to the financial crisis of 2008, Model Risk Management within the financial services industry was driven by industry best practices rather than regulatory standards(which brings to mind the saying “a fox guarding the hen house”). A purposeful MLOps strategy can provide exactly this.

Risk 111

Risk Modeling IT Risk Management 111

DataKitchen

MAY 10, 2021

Some will argue that observability is nothing more than testing and monitoring applications using tests, metrics, logs, and other artifacts. Since 2008, teams working for our founding team and our customers have delivered 100s of millions of data sets, dashboards, and models with almost no errors. Tie tests to alerts.

Testing 214

Testing Manufacturing Data Quality Statistics 214

O'Reilly on Data

JULY 15, 2019

A look at how guidelines from regulated industries can help shape your ML strategy. 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.

Machine Learning 38

Machine Learning Management Enterprise Risk Management 38

Domino Data Lab

AUGUST 8, 2019

2008 – Financial crisis : scientists flee Wall St. Another key point: troubleshooting edge cases for models in production—which is often where ethics and data meet, as far as regulators are concerned—requires much more sophistication in statistics than most data science teams tend to have. It’s a quick way to clear the room.

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

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. In the past decade, a lot of ideas and technologies have come out of the DevOps movement: the source repository as the single source of truth, rapid automated deployment, constant testing, and more.

Machine Learning 363

Machine Learning Software Testing Technology 363