Deep Learning 2019/2020 (QHD 1920 - Video & Folien)

Deep Learning 2019/2020 (QHD 1920 - Video & Folien)

Podcast by Prof. Dr. Andreas Maier Prof. Dr. Andreas Maier

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 networks loss functions and optimization strategies convolutional neural networks (CNNs) activation functions regularization strategies common practices for training and evaluating neural networks visualization of networks and results common architectures, such as LeNet, Alexnet, VGG, GoogleNet recurrent neural networks (RNN, TBPTT, LSTM, GRU) deep reinforcement learning unsupervised learning (autoencoder, RBM, DBM, VAE) generative adversarial networks (GANs) weakly supervised learning applications 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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Kaikki jaksot

14 jaksot
episode 14 - Deep Learning 2019/2020 artwork
14 - Deep Learning 2019/2020

03. helmik. 2020 - 1 h 9 min
episode 13 - Deep Learning 2019/2020 artwork
13 - Deep Learning 2019/2020

27. tammik. 2020 - 1 h 17 min
episode 12 - Deep Learning 2019/2020 artwork
12 - Deep Learning 2019/2020

20. tammik. 2020 - 1 h 10 min
episode 11 - Deep Learning 2019/2020 artwork
11 - Deep Learning 2019/2020

13. tammik. 2020 - 1 h 17 min
episode 10 - Deep Learning 2019/2020 artwork
10 - Deep Learning 2019/2020

06. tammik. 2020 - 1 h 25 min
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