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DC Field | Value | Language |
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dc.contributor.author | Skansi, Sandro | - |
dc.date.accessioned | 2021-08-23T02:42:32Z | - |
dc.date.available | 2021-08-23T02:42:32Z | - |
dc.date.issued | 2018 | - |
dc.identifier.isbn | 978-3-319-73003-5 | - |
dc.identifier.isbn | 978-3-319-73004-2 (eBook) | - |
dc.identifier.uri | http://thuvien.ued.udn.vn/handle/TVDHSPDN_123456789/57959 | - |
dc.description | 196 p. | vi |
dc.description.abstract | This book is intended to be a first introduction to deep learning. Deep learning is a special kind of learning with deep artificial neural networks, although today deep learning and artificial neural networks are considered to be the same field. Artificial neural networks are a subfield of machine learning which is in turn a subfield of both statistics and artificial intelligence (AI). Artificial neural networks are vastly more popular in artificial intelligence than in statistics. Deep learning today is not happy with just addressing a subfield of a subfield, but tries to make a run for the whole AI. An increasing number of AI fields like reasoning and planning, which were once the bastions of logical AI (also called the Good Old-Fashioned AI, or GOFAI), are now being tackled successfully by deep learning. In this sense, one might say that deep learning is an approach in AI, and not just a subfield of a subfield of AI. | vi |
dc.description.tableofcontents | From Logic to Cognitive Science; Mathematical and Computational Prerequisites; Machine Learning Basics; Feedforward Neural Networks; Modifications and Extensions to a Feed-Forward Neural Network; Convolutional Neural Networks; Recurrent Neural Networks; Autoencoders... | vi |
dc.language.iso | en_US | vi |
dc.publisher | Springer | vi |
dc.relation.ispartofseries | Undergraduate Topics in Computer Science; | - |
dc.subject | Calculus, logical | vi |
dc.subject | Intelligence, Artificial | vi |
dc.title | Introduction to Deep Learning: From Logical Calculus to Artificial Intelligence | vi |
dc.type | Book | vi |
Appears in Collections: | Computer science |
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