eBook - Responsible Data Science
Available Exclusively as an eBook | Part of the AI Collection | Only for Institutional Purchase | Publication Year: 2021
Description
Responsible Data Science addresses ethical issues in data science, focusing on bias, injustice, and discrimination caused by opaque algorithms. It teaches how to improve model transparency, diagnose bias, and audit projects to ensure fairness and minimize harm, with practical guidance for practitioners, managers, and technical professionals.
Table of Contents
1. Introduction to Responsible Data Science
2. Ethical Issues in Data Science
3. Understanding and Improving Model Transparency
4. Diagnosing Bias and Unfairness in Models
5. Auditing Data Science Projects for Fairness
6. Implementing Ethical Data Science Solutions
7. Case Studies and Applications