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Responsible AI Made Easy with TensorFlow. The Ultimate Roadmap to Ethical AI: A Practical Guide to AI Fairness, Accountability, and Transparency

Język publikacji: angielskim
Responsible AI Made Easy with TensorFlow. The Ultimate Roadmap to Ethical AI: A Practical Guide to AI Fairness, Accountability, and Transparency Emmanuel Klu, Sameer Sethi - okladka książki

Responsible AI Made Easy with TensorFlow. The Ultimate Roadmap to Ethical AI: A Practical Guide to AI Fairness, Accountability, and Transparency Emmanuel Klu, Sameer Sethi - okladka książki

Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
421
Looking to build machine learning models that are both accurate and fair? Look no further than “Responsible AI Made Easy with TensorFlow”! This hands-on guide will show you how to use TensorFlow, the popular open-source ML platform, to create AI-enabled products that prioritize fairness, accountability, and transparency.
Using real-world case studies and practical code examples, you will learn the principles of responsible AI and how to apply them in your projects. You will take a step-by-step approach through the ML development workflow, with practical guidance on how you can make responsible choices at every stage. Further, you will gain expertise in cutting-edge techniques for preprocessing data and optimizing models for fair and equitable outcomes. This book also discusses broader issues at the intersection of AI and society. It explores critical socio-technical topics including governance, accountability, problem understanding, human factors, deployment, and monitoring of ML models.
By the end of this book, with clear explanations, engaging examples, and practical advice, you will be able to responsibly build and deploy ML models into society - all while having fun along the way!

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O autorach książki

Emmanuel Klu is a software engineer with over a decade of experience in data, reliability, and machine learning. He currently works at Google Research, using a data-centric and systems-thinking lens to explore responsible AI topics like fairness, bias and safety. Emmanuel studied Computer Science and Psychology at the Illinois Institute of Technology in Chicago.
Sameer Sethi has spent more than 10 years developing products and platforms on network design, data warehousing and machine learning. Currently at Google Research, he focuses on building fair, equitable, and safe machine learning-driven solutions using participatory approaches. Sameer holds a Bachelor of Engineering in Information and Communications from Dublin City University, along with a Master of Technology in Communications from ITM University.

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