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1. Valuable resource for anyone working in machine learning
   This book is a page-turner for anyone who wants to dive deep into the world of machine learning and AI ethics. The authors did an excellent job of breaking down complex concepts into easy-to-digest nuggets of knowledge.
   The chapters are well-structured and follow a logical flow that builds upon previous concepts. The authors use real-world code examples and case studies to illustrate how these concepts can be applied in practice. This makes it easy to understand the practical implications of the principles being discussed.
   One of the things I appreciated most about this book is the attention paid to fairness and bias in AI. The authors highlight the importance of ensuring that machine learning models are not perpetuating existing biases in society. They provide actionable steps that ML practitioners can take to address bias and ensure fairness in their models.
   Overall, I highly recommend this book to anyone who wants to develop a deep understanding of ethical and trustworthy AI.

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2. Great for ML Engineers
   I bought this book because I work as a machine learning engineer, and I’d like to become more knowledgeable about its responsible use. This book is great for that. It takes a very practical approach to the subject, going into clear detail. It covers privacy and fairness, topics which come up often when you use an ML model in the real world. Good mix of theory and practice. It’s definitely a book I’ll be reaching for as a reference in the future.

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3. A great introduction to a lot of esoteric subjects in ML
   This is one of the best AI safety books with code out there……on the grounds of being one of the very few AI safety books with ANY code examples. This book does assume one already knows how to put together a neural network in PyTorch. That being said, it does a pretty good job in being consistent with the use of PyTorch and HuggingFace for the examples.
   Disclaimer: I am one of the authors of this book.

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4. Great resource!
   This book is perfect for my machine learning consultants. Highly recommend!

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5. An excellent resource for anyone involved in the field of AI and machine learning
   One of the things I liked most about this book is its emphasis on the ethical considerations of machine learning. The authors do a great job of highlighting the potential biases and ethical challenges that arise when working with large datasets and cutting edge algorithms.

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6. Love the code examples
   Very practical book that is up to date with a rapidly changing field, great for effective altruists and others concerned with grounding ethics in actionable guidelines.

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