Deep Learning and Practice with MindSpore

Deep Learning and Practice with MindSpore

von

Chen, LeiZeng, YunhuiÜbersetzung

BuchKartoniert, Paperback

CHF208.00

Beschreibung

This book systematically introduces readers to the theory of deep learning and explores its practical applications based on the MindSpore AI computing framework. Divided into 14 chapters, the book covers deep learning, deep neural networks (DNNs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), unsupervised learning, deep reinforcement learning, automated machine learning, device-cloud collaboration, deep learning visualization, and data preparation for deep learning. To help clarify the complex topics discussed, this book includes numerous examples and links to online resources.

Weitere Beschreibungen

Details

ISBN/GTIN978-981-16-2235-9

ProduktartBuch

EinbandKartoniert, Paperback

Verlag

Springer Nature Singapore

Erscheinungsdatum19.08.2022

Auflage1st ed. 2021

ReiheCognitive Intelligence and Robotics

Seiten412 Seiten

SpracheEnglisch

MasseBreite 155 mm, Höhe 235 mm, Dicke 23 mm

Gewicht622 g

Artikel-Nr.25711870

KatalogBuchzentrum

Datenquelle-Nr.40734957

Weitere Details

Reihe

Principles in Noisy Optimization

Intelligent Control

Cognitively Inspired Natural Language Processing

Intelligent Control

Web Searching and Mining

Orthogonal Image Moments for Human-Centric Visual Pattern Recognition

Multi-Body Dynamic Modeling of Multi-Legged Robots

Human Emotion Recognition from Face Images

Intrusion Detection

Orthogonal Image Moments for Human-Centric Visual Pattern Recognition

Intrusion Detection

Multi-Body Dynamic Modeling of Multi-Legged Robots

Human Emotion Recognition from Face Images

Deep Learning and Practice with Mindspore

Autonomous Underwater Vehicles

Cognitively Inspired Video Text Processing

Deep Learning and Practice with MindSpore

Large-Scale Simultaneous Localization and Mapping

Autonomous Underwater Vehicles

Cognitively Inspired Video Text Processing

Large-Scale Simultaneous Localization and Mapping

Anomaly Detection in Video Surveillance

Autor

Chen, LeiZeng, YunhuiÜbersetzung

Chen Lei is a Chair Professor of the Department of Computer Science and Engineering and the Director of the Big Data Institute at Hong Kong University of Science and Technology (HKUST). His research focuses on data-driven AI, human-powered machine learning, knowledge graphs, and data mining on social media. He has published more than 400 papers in world-renowned journals and conference proceedings and won the 2015 SIGMOD Test of Time Award. Currently, he serves as the Editor-in-Chief of the VLDB 2019 Journal, the Associate Editor-in-Chief of the IEEE TKDE Journal, and an executive member of the VLDB Endowment. He is also IEEE Fellow and ACM Distinguished Scientist.