Authors Yada Pruksachatkun, Matthew McAteer, and Subhabrata Majumdar translate best practices in the academic literature for curating datasets and building models into a blueprint for building industry-grade trusted ML systems. With this book, engineers and data scientists will gain a much-needed foundation for releasing trustworthy ML applications into a noisy, messy, and often hostile world.
You'll learn:
- Methods to explain ML models and their outputs to stakeholders
- How to recognize and fix fairness concerns and privacy leaks in an ML pipeline
- How to develop ML systems that are robust and secure against malicious attacks
- Important systemic considerations, like how to manage trust debt and which ML obstacles require human intervention
Authors Yada Pruksachatkun, Matthew McAteer, and Subhabrata Majumdar translate best practices in the academic literature for curating datasets and building models into a blueprint for building industry-grade trusted ML systems. With this book, engineers and data scientists will gain a much-needed foundation for releasing trustworthy ML applications into a noisy, messy, and often hostile world.
You'll learn:
- Methods to explain ML models and their outputs to stakeholders
- How to recognize and fix fairness concerns and privacy leaks in an ML pipeline
- How to develop ML systems that are robust and secure against malicious attacks
- Important systemic considerations, like how to manage trust debt and which ML obstacles require human intervention
![Practicing Trustworthy Machine Learning: Consistent, Transparent, and Fair AI Pipelines](http://img.images-bn.com/static/redesign/srcs/images/grey-box.png?v11.10.4)
Practicing Trustworthy Machine Learning: Consistent, Transparent, and Fair AI Pipelines
300![Practicing Trustworthy Machine Learning: Consistent, Transparent, and Fair AI Pipelines](http://img.images-bn.com/static/redesign/srcs/images/grey-box.png?v11.10.4)
Practicing Trustworthy Machine Learning: Consistent, Transparent, and Fair AI Pipelines
300Product Details
ISBN-13: | 9781098120276 |
---|---|
Publisher: | O'Reilly Media, Incorporated |
Publication date: | 02/28/2023 |
Pages: | 300 |
Product dimensions: | 6.90(w) x 8.70(h) x 0.70(d) |