Deep Learning - Plain Version 2020 /CourseID:1384

Detailed information

Keywords: Perceptron Introduction artificial intelligence deep learning machine learning pattern recognition

Most recent entry on 2020-07-10 

Organisational Unit

Lehrstuhl für Machine Intelligence

Recording type

Vorlesungsreihe

Via

Free

Language

English

 

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.

 

Associated Clips

Episode
Title
Lecturer
Updated
Via
Duration
Media
1
Deep Learning - Introduction Part 1
Prof. Dr. Andreas Maier
2020-05-27
Free
00:15:10
2
Deep Learning - Introduction Part 2
Prof. Dr. Andreas Maier
2020-05-27
Free
00:17:39
3
Deep Learning - Introduction Part 3
Prof. Dr. Andreas Maier
2020-05-27
Free
00:07:55
4
Deep Learning - Introduction Part 4
Prof. Dr. Andreas Maier
2020-05-27
Free
00:13:30
5
Deep Learning - Introduction Part 5
Prof. Dr. Andreas Maier
2020-05-27
Free
00:05:57
6
Deep Learning - Feedforward Networks Part 1
Prof. Dr. Andreas Maier
2020-05-28
Free
00:17:38
7
Deep Learning - Feedforward Networks Part 2
Prof. Dr. Andreas Maier
2020-05-28
Free
00:11:22
8
Deep Learning - Feedforward Networks Part 3
Prof. Dr. Andreas Maier
2020-05-28
Free
00:18:37
9
Deep Learning - Feedforward Networks Part 4
Prof. Dr. Andreas Maier
2020-05-28
Free
00:09:18
10
Deep Learning - Loss and Optimization Part 1
Prof. Dr. Andreas Maier
2020-05-29
Free
00:14:48
11
Deep Learning - Loss and Optimization Part 2
Prof. Dr. Andreas Maier
2020-05-30
Free
00:17:50
12
Deep Learning - Loss and Optimization Part 3
Prof. Dr. Andreas Maier
2020-05-30
Free
00:22:16
13
Deep Learning - Activations, Convolutions, and Pooling Part 1
Prof. Dr. Andreas Maier
2020-05-30
Free
00:09:30
14
Deep Learning - Activations, Convolutions, and Pooling Part 2
Prof. Dr. Andreas Maier
2020-05-30
Free
00:11:35
15
Deep Learning - Activations, Convolutions, and Pooling Part 3
Prof. Dr. Andreas Maier
2020-05-30
Free
00:15:30
16
Deep Learning - Activations, Convolutions, and Pooling Part 4
Prof. Dr. Andreas Maier
2020-05-30
Free
00:08:48
17
Deep Learning - Regularization Part 1
Prof. Dr. Andreas Maier
2020-05-30
Free
00:10:35
18
Deep Learning - Regularization Part 2
Prof. Dr. Andreas Maier
2020-05-31
Free
00:13:38
19
Deep Learning - Regularization Part 3
Prof. Dr. Andreas Maier
2020-05-31
Free
00:09:18
20
Deep Learning - Regularization Part 4
Prof. Dr. Andreas Maier
2020-05-31
Free
00:09:26
21
Deep Learning - Regularization Part 5
Prof. Dr. Andreas Maier
2020-05-31
Free
00:06:23
22
Deep Learning - Common Practices Part 1
Prof. Dr. Andreas Maier
2020-05-31
Free
00:10:53
23
Deep Learning - Common Practices Part 2
Prof. Dr. Andreas Maier
2020-05-31
Free
00:08:57
24
Deep Learning - Common Practices Part 3
Prof. Dr. Andreas Maier
2020-06-01
Free
00:05:09
25
Deep Learning - Common Practices Part 4
Prof. Dr. Andreas Maier
2020-06-01
Free
00:12:14
26
Deep Learning - Architectures Part 1
Prof. Dr. Andreas Maier
2020-06-02
Free
00:16:03
27
Deep Learning - Architectures Part 2
Prof. Dr. Andreas Maier
2020-06-02
Free
00:09:45
28
Deep Learning - Architectures Part 3
Prof. Dr. Andreas Maier
2020-06-02
Free
00:12:49
29
Deep Learning - Architectures Part 4
Prof. Dr. Andreas Maier
2020-06-02
Free
00:07:34
30
Deep Learning - Architectures Part 5
Prof. Dr. Andreas Maier
2020-06-03
Free
00:07:07
31
Deep Learning - Recurrent Neural Networks Part 1
Prof. Dr. Andreas Maier
2020-06-06
Free
00:10:38
32
Deep Learning - Recurrent Neural Networks Part 2
Prof. Dr. Andreas Maier
2020-06-06
Free
00:15:33
33
Deep Learning - Recurrent Neural Networks Part 3
Prof. Dr. Andreas Maier
2020-06-06
Free
00:09:32
34
Deep Learning - Recurrent Neural Networks Part 4
Prof. Dr. Andreas Maier
2020-06-06
Free
00:09:06
35
Deep Learning - Recurrent Neural Networks Part 5
Prof. Dr. Andreas Maier
2020-06-06
Free
00:12:46
36
Deep Learning - Visualization Part 1
Prof. Dr. Andreas Maier
2020-06-09
Free
00:11:58
37
Deep Learning - Visualization Part 2
Prof. Dr. Andreas Maier
2020-06-09
Free
00:17:14
38
Deep Learning - Visualization Part 3
Prof. Dr. Andreas Maier
2020-06-09
Free
00:09:59
39
Deep Learning - Visualization Part 4
Prof. Dr. Andreas Maier
2020-06-09
Free
00:19:46
40
Deep Learning - Visualization Part 5
Prof. Dr. Andreas Maier
2020-06-09
Free
00:23:26
41
Deep Learning - Reinforcement Learning Part 1
Prof. Dr. Andreas Maier
2020-06-14
Free
00:15:18
42
Deep Learning - Reinforcement Learning Part 2
Prof. Dr. Andreas Maier
2020-06-14
Free
00:14:14
43
Deep Learning - Reinforcement Learning Part 3
Prof. Dr. Andreas Maier
2020-06-14
Free
00:17:39
44
Deep Learning - Reinforcement Learning Part 4
Prof. Dr. Andreas Maier
2020-06-14
Free
00:07:28
45
Deep Learning - Reinforcement Learning Part 5
Prof. Dr. Andreas Maier
2020-06-14
Free
00:18:48
46
Deep Learning - Unsupervised Learning Part 1
Prof. Dr. Andreas Maier
2020-06-21
Free
00:17:36
47
Deep Learning - Unsupervised Learning Part 2
Prof. Dr. Andreas Maier
2020-06-21
Free
00:19:50
48
Deep Learning - Unsupervised Learning Part 3
Prof. Dr. Andreas Maier
2020-06-21
Free
00:11:26
49
Deep Learning - Unsupervised Learning Part 4
Prof. Dr. Andreas Maier
2020-06-21
Free
00:09:05
50
Deep Learning - Unsupervised Learning Part 5
Prof. Dr. Andreas Maier
2020-06-21
Free
00:18:09
51
Deep Learning - Segmentation and Object Detection Part 1
Prof. Dr. Andreas Maier
2020-06-28
Free
00:14:16
52
Deep Learning - Segmentation and Object Detection Part 2
Prof. Dr. Andreas Maier
2020-06-28
Free
00:14:24
53
Deep Learning - Segmentation and Object Detection Part 3
Prof. Dr. Andreas Maier
2020-06-28
Free
00:13:52
54
Deep Learning - Segmentation and Object Detection Part 4
Prof. Dr. Andreas Maier
2020-06-28
Free
00:08:11
55
Deep Learning - Segmentation and Object Detection Part 5
Prof. Dr. Andreas Maier
2020-06-28
Free
00:07:13
56
Deep Learning - Weakly and Self-Supervised Learning Part 1
Prof. Dr. Andreas Maier
2020-07-05
Free
00:12:13
57
Deep Learning - Weakly and Self-Supervised Learning Part 2
Prof. Dr. Andreas Maier
2020-07-05
Free
00:04:40
58
Deep Learning - Weakly and Self-Supervised Learning Part 3
Prof. Dr. Andreas Maier
2020-07-05
Free
00:15:55
59
Deep Learning - Weakly and Self-Supervised Learning Part 4
Prof. Dr. Andreas Maier
2020-07-05
Free
00:15:17
60
Deep Learning - Graph Deep Learning Part 1
Prof. Dr. Andreas Maier
2020-07-10
Free
00:11:07
61
Deep Learning - Graph Deep Learning Part 2
Prof. Dr. Andreas Maier
2020-07-10
Free
00:10:45
62
Deep Learning - Known Operator Learning Part 1
Prof. Dr. Andreas Maier
2020-07-10
Free
00:07:57
63
Deep Learning - Known Operator Learning Part 2
Prof. Dr. Andreas Maier
2020-07-10
Free
00:10:58
64
Deep Learning - Known Operator Learning Part 3
Prof. Dr. Andreas Maier
2020-07-10
Free
00:16:52
65
Deep Learning - Known Operator Learning Part 4
Prof. Dr. Andreas Maier
2020-07-10
Free
00:24:50

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