Instant download Deep Learning Concepts and Architectures pdf, docx, kindle format all chapters after payment. ISBN(s): 9783030317560, 3030317560
Product details:
- ISBN 10: 3030317560
- ISBN 13: 9783030317560
- Author: Witold
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.
Table contents:
- Deep Learning Architectures
- Theoretical Characterization of Deep Neural Networks
- Scaling Analysis of Specialized Tensor Processing Architectures for Deep Learning Models
- Assessment of Autoencoder Architectures for Data Representation
- The Encoder-Decoder Framework and Its Applications
- Deep Learning for Learning Graph Representations
- Deep Neural Networks for Corrupted Labels
- Constructing a Convolutional Neural Network with a Suitable Capacity for a Semantic Segmentation Task
- Using Convolutional Neural Networks to Forecast Sporting Event Results
- Heterogeneous Computing System for Deep Learning
- Progress in Neural Network Based Statistical Language Modeling
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