Der er 9 underkategorier
Neurale net og fuzzy systemer
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Artificial Neural Networks and Machine Learning – ICANN 2016: 25th International Conference on Artificial Neural Networks, Barcelona, Spain, September 6-9, 2016, Proceedings, Part I (Bog, Paperback / softback, Engelsk)The two volume set, LNCS 9886 + 9887, constitutes the proceedings of the... Læs mere
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Artificial Neural Networks and Machine Learning – ICANN 2017: 26th International Conference on Artificial Neural Networks, Alghero, Italy, September 11-14, 2017, Proceedings, Part II (Bog, Paperback / softback, Engelsk)The two volume set, LNCS 10613 and 10614, constitutes the proceedings of... Læs mere
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Artificial Neural Networks and Machine Learning – ICANN 2017: 26th International Conference on Artificial Neural Networks, Alghero, Italy, September 11-14, 2017, Proceedings, Part I (Bog, Paperback / softback, Engelsk)The two volume set, LNCS 10613 and 10614, constitutes the proceedings of... Læs mere
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Learn Keras for Deep Neural Networks: A Fast-Track Approach to Modern Deep Learning with Python (Bog, Paperback / softback, Engelsk)Levering: Skaffevare (forvent 14 - 30 hverdage) -
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Not Exactly: In Praise of Vagueness (Bog, Paperback / softback, Engelsk)Our lives are full of inexactitude. We say a person is tall or an action is just without the precision of measurement on a dial. In this engaging account, Kees van... Læs mere
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TensorFlow for Deep Learning: From Linear Regression to Reinforcement Learning (Bog, Paperback / softback, Engelsk)Learn how to solve challenging machine learning problems with TensorFlow, Google’s revolutionary new software library for deep learning. If you have some background in basic linear algebra and calculus, this practical book introduces machine-learning fundamentals.
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Self-Learning and Adaptive Algorithms for Business Applications: A Guide to Adaptive Neuro-Fuzzy Systems for Fuzzy Clustering Under Uncertainty Conditions (Bog, Paperback / softback, Engelsk)In this guide designed for researchers and students of computer science, readers will find a resource for how to apply methods that work on real-life problems to their challenging applications, and a go-to work that makes fuzzy clustering issues and aspects clear.
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