Search
×
FR

Placeholder headline

This is just a placeholder headline

API STD 521: Guide for Pressure-relieving and Depressuring Systems – Edition 6

$

682

BUY NOW

Placeholder headline

This is just a placeholder headline

API STD 653: Tank Inspection, Repair, Alteration, and Reconstruction – Edition 4

$

507

BUY NOW

Placeholder headline

This is just a placeholder headline

CSA Z662:19 – Oil and gas pipeline systems

$

1197

BUY NOW

Placeholder headline

This is just a placeholder headline

CSA Z341 Series-18: Storage of hydrocarbons in underground formations

$

878

BUY NOW

Placeholder headline

This is just a placeholder headline

CSA Z246.2-14 – Emergency preparedness and response for petroleum and natural gas industry systems

$

596

BUY NOW

Placeholder headline

This is just a placeholder headline

CSA Z341 Series:22 – Storage of hydrocarbons in underground formations

$

878

BUY NOW

Placeholder headline

This is just a placeholder headline

CSA Z731-09 (R2014) – Emergency Preparedness and Response

$

177

BUY NOW

Placeholder headline

This is just a placeholder headline

CSA Z662:23 – Oil and gas pipeline systems

$

1197

BUY NOW

Placeholder headline

This is just a placeholder headline

CSA Z341 Series:26 – Storage of Hydrocarbons in underground formations

$

878

BUY NOW

Placeholder headline

This is just a placeholder headline

CSA B51:24 Boiler, Pressure Vessel, and Pressure Piping Code

$

389

BUY NOW

ISO 12791:2024

ISO 12791:2024 Information technology – Artificial intelligence – Treatment of unwanted bias in classification and regression machine learning tasks

CDN $251.00

Description

This document describes how to address unwanted bias in AI systems that use machine learning to conduct classification and regression tasks. This document provides mitigation techniques that can be applied throughout the AI system life cycle in order to treat unwanted bias. This document is applicable to all types and sizes of organization.

Edition

1

Published Date

2024-10-31

Status

PUBLISHED

Pages

24

Language Detail Icon

English

Format Secure Icon

Secure PDF

Abstract

This document describes how to address unwanted bias in AI systems that use machine learning to conduct classification and regression tasks. This document provides mitigation techniques that can be applied throughout the AI system life cycle in order to treat unwanted bias. This document is applicable to all types and sizes of organization.

Previous Editions

Can’t find what you are looking for?

Please contact us at: