Andreas Maier

253 to 189 of 189

25NOV 2020
Pattern Recognition WS 20/21
Watch now: Pattern Recognition: Episode 15 – Linear Discriminant Analysis – Examples (WS 20/21)
In this video, we look into some example applications of LDA and PCA. Watch on:FAU TVYouTube
Read more about Watch now: Pattern Recognition: Episode 15 – Linear Discriminant Analysis – Examples (WS 20/21)
25NOV 2020
Deep Learning WS 20/21
Watch now: Deep Learning: Regularization – Part 2 (WS 20/21)
This video discusses classical regularization techniques such as early stopping using a validation set, augmentation, and maximum a-posteriori methods that expand the loss function using a regularization term. Watch on:FAU TVFAU TV (no memes)YouTube Read the Transcript (Summer 2020) at:LMETowards Data Science
Read more about Watch now: Deep Learning: Regularization – Part 2 (WS 20/21)
24NOV 2020
Pattern Recognition WS 20/21
Watch now: Pattern Recognition: Episode 14 – Linear Discriminant Analysis – Original Formulation (WS 20/21)
In this video, we have a look at the original formulation of LDA as Fisher Transform. Watch on:FAU TVYouTube
Read more about Watch now: Pattern Recognition: Episode 14 – Linear Discriminant Analysis – Original Formulation (WS 20/21)
24NOV 2020
Deep Learning WS 20/21
Watch now: Deep Learning: Regularization – Part 1 (WS 20/21)
This video discusses the problem of over- and underfitting. In order to get a better understanding, we explore the bias-variance trade-off and look into the effects of training data size and the number of parameters. Watch on:FAU TVFAU TV (no memes)YouTube Read the Transcript (Summer 2020) at:LMETowards Data Science
Read more about Watch now: Deep Learning: Regularization – Part 1 (WS 20/21)
23NOV 2020
Pattern Recognition WS 20/21
Watch now: Pattern Recognition: Episode 13 – Linear Discriminant Analysis – Rank-Reduced Form (WS 20/21)
In this video, we introduce a rank-reduced version of the LDA. Watch on:FAU TVYouTube
Read more about Watch now: Pattern Recognition: Episode 13 – Linear Discriminant Analysis – Rank-Reduced Form (WS 20/21)
23NOV 2020
Deep Learning WS 20/21
Watch now: Deep Learning: Deep Learning: Activations, Convolutions, and Pooling – Part 4 (WS 20/21) (WS 20/21)
This video presents max and average pooling, introduces the concept of fully convolutional networks, and hints on how this is used to build deep networks. Watch on:FAU TVFAU TV (no memes)YouTube Read the Transcript (Summer 2020) at:LMETowards Data Science
Read more about Watch now: Deep Learning: Deep Learning: Activations, Convolutions, and Pooling – Part 4 (WS 20/21) (WS 20/21)