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Deep Learning - Plain Version 2020 (QHD 1920)Episode from the podcastDeep Learning - Plain Version 2020 (QHD 1920)
60 - Deep Learning - Graph Deep Learning Part 1 2020

60 - Deep Learning - Graph Deep Learning Part 1 2020

Released Thursday, 9th July 2020
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60 - Deep Learning - Graph Deep Learning Part 1 2020

60 - Deep Learning - Graph Deep Learning Part 1 2020

60 - Deep Learning - Graph Deep Learning Part 1 2020

60 - Deep Learning - Graph Deep Learning Part 1 2020

Thursday, 9th July 2020
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From The Podcast

 Deep Learning (DL) has attracted much interest in a wide range of applications such as image recognition, speech recognition, and artificial intelligence, both from academia and industry. This lecture introduces the core elements of neural networks and deep learning, it comprises:(multilayer) perceptron, backpropagation, fully connected neural networksloss functions and optimization strategiesconvolutional neural networks (CNNs)activation functionsregularization strategiescommon practices for training and evaluating neural networksvisualization of networks and resultscommon architectures, such as LeNet, Alexnet, VGG, GoogleNetrecurrent neural networks (RNN, TBPTT, LSTM, GRU)deep reinforcement learningunsupervised learning (autoencoder, RBM, DBM, VAE)generative adversarial networks (GANs)weakly supervised learningapplications of deep learning (segmentation, object detection, speech recognition, ...)The accompanying exercises will provide a deeper understanding of the workings and architecture of neural networks.

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