Applied Machine Learning Explainability Techniques: Make ML models explainable and trustworthy for practical applications PDF
306 Pages·2022·7.577 MB·other
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Preview Applied Machine Learning Explainability Techniques: Make ML models explainable and trustworthy for practical applications
Description:
Who this book is for
This book is designed for scientists, researchers, engineers, architects, and managers who are actively engaged in the field of Machine Learning and related areas. In general, anyone who is interested in problem-solving using AI would be benefited from this book. The readers are recommended to have a foundational knowledge of Python, Machine Learning, Deep Learning, and Data Science. This book is ideal for readers who are working in the following roles
Data and AI Scientists
AI/ML Engineers
AI/ML Product Managers
AI Product Owners
AI/ML Researchers
User experience and HCI Researchers
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Most books are stored in the elastic cloud where traffic is expensive. For this reason, we have a limit on daily download.
