Pytorch deep learning and graph neural по низким ценам

PyTorch Deep Learning and Graph Neural Networks: Foundations (Vol 1)

PyTorch Deep Learning and Graph Neural Networks: Foundations (Vol 1)


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Gene Cheung Graph Spectral Image Processing

Gene Cheung Graph Spectral Image Processing


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Graph spectral image processing is the study of imaging data from a graph frequency perspective. Modern image sensors capture a wide range of visual data including high spatial resolution/high bit-depth 2D images and videos, hyperspectral images, light field images and 3D point clouds. The field of
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PyTorch Deep Learning Practical Guide

PyTorch Deep Learning Practical Guide


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Deep Dive into Graph Neural Networks (GNN) Tutorial

Deep Dive into Graph Neural Networks (GNN) Tutorial


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Deep Learning, PyTorch, and Large Language Models: A Practical Guide

Deep Learning, PyTorch, and Large Language Models: A Practical Guide


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PyTorch Deep Learning Practice Handbook, 2nd Edition

PyTorch Deep Learning Practice Handbook, 2nd Edition


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PyTorch Deep Learning Programming Guide: Volume I

PyTorch Deep Learning Programming Guide: Volume I


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Deep Learning PyTorch Computer Vision Practical Guide

Deep Learning PyTorch Computer Vision Practical Guide


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PyTorch Deep Learning: Introduction & Practice (2nd Edition)

PyTorch Deep Learning: Introduction & Practice (2nd Edition)


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Группа авторов Computational Analysis and Deep Learning for Medical Care

Группа авторов Computational Analysis and Deep Learning for Medical Care


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This book discuss how deep learning can help healthcare images or text data in making useful decisions”. For that, the need of reliable deep learning models like Neural networks, Convolutional neural network, Backpropagation, Recurrent neural network is increasing in medical image processing, i.e.,
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Nan Zheng Learning in Energy-Efficient Neuromorphic Computing: Algorithm and Architecture Co-Design

Nan Zheng Learning in Energy-Efficient Neuromorphic Computing: Algorithm and Architecture Co-Design


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Explains current co-design and co-optimization methodologies for building hardware neural networks and algorithms for machine learning applications This book focuses on how to build energy-efficient hardware for neural networks with learning capabilities—and provides co-design and co-optimization
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Savo G. Glisic Artificial Intelligence and Quantum Computing for Advanced Wireless Networks

Savo G. Glisic Artificial Intelligence and Quantum Computing for Advanced Wireless Networks


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ARTIFICIAL INTELLIGENCE AND QUANTUM COMPUTING FOR ADVANCED WIRELESS NETWORKS A practical overview of the implementation of artificial intelligence and quantum computing technology in large-scale communication networks Increasingly dense and flexible wireless networks require the use of
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