Deep Learning 2018/2019

Details

Schlüsselworte: bernoulli deep batch visualization backpropagation inception block normalization unsupervised label pattern DeepDream Go Detection Siri Alexa machine neuronal multi-layer abstraction

Letzter Beitrag vom 2019-01-08 

Fakultät

Lehrstuhl für Informatik 5 (Mustererkennung)

Aufzeichnungsart

Vorlesungsreihe

Zugang

Frei

Sprache

Englisch

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, ...)

Zugehörige Einzelbeiträge

Folge
Titel
Lehrende(r):
Aktualisiert
Zugang
Dauer
Medien
1
Prof. Dr. Andreas Maier
2018-10-16
Frei
01:27:46
2
Prof. Dr. Andreas Maier
2018-10-23
Frei
01:24:57
3
Tobias Würfl
2018-10-30
Frei
01:38:06
4
Prof. Dr. Andreas Maier
2018-11-06
Frei
01:17:15
5
MA Katharina Breininger
2018-11-13
Frei
01:04:36
6
Prof. Dr. Andreas Maier
2018-11-20
Frei
01:04:15
7
Prof. Dr. Andreas Maier
2018-11-27
Frei
01:07:41
8
Prof. Dr. Andreas Maier
2018-12-04
Frei
01:00:59
9
Prof. Dr. Andreas Maier
2018-12-11
Frei
01:06:17
10
Prof. Dr. Andreas Maier
2018-12-18
Frei
01:07:23
11
MA Katharina Breininger, MA Katharina Breininger
2019-01-08
Frei
01:22:46

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