Название: MATLAB Deep Learning Toolbox Reference (R2022a)
Автор: Mark Hudson Beale, Martin T. Hagan, Howard B. Demuth
Издательство: The MathWorks, Inc.
Год: 2022
Формат: PDF
Страниц: 2314
Размер: 14,7 Mb
Язык: English

Deep Learning Toolbox provides a framework for designing and implementing deep 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. You can build network architectures such as generative adversarial networks (GANs) and Siamese networks using automatic differentiation, custom training loops, and shared weights. With the Deep Network Designer app, you can design, analyze, and train networks graphically. The Experiment Manager app helps you manage multiple deep learning experiments, keep track of training parameters, analyze results, and compare code from different experiments. You can visualize layer activations and graphically monitor training progress.