ISBN-13: 9781681236292, 978-1681236292. The book is divided into three parts. Part II presents the results of four exploratory case studies. These studies reproduce the results of Part I with a more diverse sample of students; under new conditions (a public debate, peer discussions, and group interviews); and with new research prompts (model-building software, bridging tasks, and elicitation strategies).
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For the rest of us however, deep learning is still a pretty complex and difficult subject to grasp. This book uses exposition and examples to help you understand major concepts in this complicated field.
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Their improved accuracy, effectiveness in handling large data as well as reduced redundancy have major impact on growing application in the relevant field creating a demand for such a book in the market.
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ISBN-13: 9781563770487, 978-1563770487. Format: Paperback.
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[Don’t forget to check with neighbours / sorting office / outhouses if you are out a lot! ]]>.
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The content of this book has been organized such that each chapter can be read independently from the others.
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ISBN-13: 9783031206382, 978-3031206382. This book is a comprehensive curation, exposition and illustrative discussion of recent research tools for interpretability of deep learning models, with a focus on neural network architectures.
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