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OverviewNEURAL Network Toolbox (Deep Learning Toolbox from version 18) provides a framework for designing and implementing neural networks with algorithms, pretrained models, and apps. You can use convolutional neural networks (ConvNets, CNNs) and long short-term memory (LSTM) networks to perform classification and regression on image, time-series, and text data. Apps and plots help you visualize activations, edit network architectures, and monitor training progress.For small training sets, you can perform transfer learning with pretrained deep network models (including SqueezeNet, Inception-v3, ResNet-101, GoogLeNet, and VGG-19) and models imported from TensorFlow Keras and Caffe.To speed up training on large datasets, you can distribute computations and data across multicore processors and GPUs on the desktop (with Parallel Computing Toolbox), or scale up to clusters and clouds, including Amazon EC2 P2, P3, and G3 GPU instances (with MATLAB Parallel Server). Full Product DetailsAuthor: C PerezPublisher: Independently Published Imprint: Independently Published Dimensions: Width: 15.20cm , Height: 1.90cm , Length: 22.90cm Weight: 0.490kg ISBN: 9781093526677ISBN 10: 109352667 Pages: 334 Publication Date: 10 April 2019 Audience: General/trade , General Format: Paperback Publisher's Status: Active Availability: Available To Order ![]() We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately. Table of ContentsReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |