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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Spis treści

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

• 1. What is Responsible AI?
• 2. Fairness & Privacy
• 3. Privacy`
• 4. Robustness & Explainability
• 5. An end-to-end Responsible AI pipeline
• 6. Why data choices matter
• 7. Evaluating ML datasets
• 8. Remediating ML datasets
• 9. Why model choices matter
• 10. Evaluating ML models
• 11. Remediating ML models
• 12. AI Governance
• 13. Deployment and Monitoring
• 14. Humans-in-the-Loop
• 15. Wrapping Up