Most ebook files are in PDF format, so you can easily read them using various software such as Foxit Reader or directly on the Google Chrome browser.
Some ebook files are released by publishers in other formats such as .awz, .mobi, .epub, .fb2, etc. You may need to install specific software to read these formats on mobile/PC, such as Calibre.
Please read the tutorial at this link: https://ebookbell.com/faq
We offer FREE conversion to the popular formats you request; however, this may take some time. Therefore, right after payment, please email us, and we will try to provide the service as quickly as possible.
For some exceptional file formats or broken links (if any), please refrain from opening any disputes. Instead, email us first, and we will try to assist within a maximum of 6 hours.
EbookBell Team
4.0
6 reviewsAre human decisions less biased than automated ones? AI is increasingly showing up in highly sensitive areas such as healthcare, hiring, and criminal justice. Many people assume that using data to automate decisions would make everything fair, but that’s not the case. In this report, business, analytics, and data science leaders will examine the challenges of defining fairness and reducing unfair bias throughout the machine learning pipeline.
Trisha Mahoney, Kush R. Varshney, and Michael Hind from IBM explain why you need to engage early and authoritatively when building AI you can trust. You’ll learn how your organization should approach fairness and bias, including trade-offs you need to make between model accuracy and model bias. This report also introduces you to AI Fairness 360, an extensible open source toolkit for measuring, understanding, and reducing AI bias.
