Deep Learning Concepts and Architectures 1st edition by Witold Pedrycz ISBN 3030317560 9783030317560

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ISBN 10:  3030317560
ISBN 13: 9783030317560
Author: Witold Pedrycz

This book introduces readers to the fundamental concepts of deep learning and offers practical insights into how this learning paradigm supports automatic mechanisms of structural knowledge representation. It discusses a number of multilayer architectures giving rise to tangible and functionally meaningful pieces of knowledge, and shows how the structural developments have become essential to the successful delivery of competitive practical solutions to real-world problems. The book also demonstrates how the architectural developments, which arise in the setting of deep learning, support detailed learning and refinements to the system design. Featuring detailed descriptions of the current trends in the design and analysis of deep learning topologies, the book offers practical guidelines and presents competitive solutions to various areas of language modeling, graph representation, and forecasting.

Deep Learning Concepts and Architectures 1st Table of contents:

1. Deep Learning Architectures
2. Theoretical Characterization of Deep Neural Networks
3. Scaling Analysis of Specialized Tensor Processing Architectures for Deep Learning Models
4. Assessment of Autoencoder Architectures for Data Representation
5. The Encoder-Decoder Framework and Its Applications
6. Deep Learning for Learning Graph Representations
7. Deep Neural Networks for Corrupted Labels
8. Constructing a Convolutional Neural Network with a Suitable Capacity for a Semantic Segmentation Task
9. Using Convolutional Neural Networks to Forecast Sporting Event Results
10. Heterogeneous Computing System for Deep Learning
11. Progress in Neural Network Based Statistical Language Modeling
12. Back Matter

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Tags: Witold Pedrycz, Deep Learning, Concepts and Architectures