Andreas Maier

259 to 192 of 192

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)
22NOV 2020
Lecture Notes in Pattern Recognition
Lecture Notes in Pattern Recognition: Episode 4 – Basics – The Optimal Classifier
These are the lecture notes for FAU’s YouTube Lecture “Pattern Recognition“. This is a full transcript of the lecture video & matching slides. We hope, you enjoy this as much as the videos. Of course, this transcript was created with deep learning techniques largely automatically and only minor manual modifications were performed. Try it yourself! If you […]
Read more about Lecture Notes in Pattern Recognition: Episode 4 – Basics – The Optimal Classifier
22NOV 2020
Lecture Notes in Pattern Recognition
Lecture Notes in Pattern Recognition: Episode 3 – Basics – Bayes Theorem
These are the lecture notes for FAU’s YouTube Lecture “Pattern Recognition“. This is a full transcript of the lecture video & matching slides. We hope, you enjoy this as much as the videos. Of course, this transcript was created with deep learning techniques largely automatically and only minor manual modifications were performed. Try it yourself! If you […]
Read more about Lecture Notes in Pattern Recognition: Episode 3 – Basics – Bayes Theorem
21NOV 2020
Lecture Notes in Pattern Recognition
Lecture Notes in Pattern Recognition: Episode 2 – Pattern Recognition Postulates
These are the lecture notes for FAU’s YouTube Lecture “Pattern Recognition“. This is a full transcript of the lecture video & matching slides. We hope, you enjoy this as much as the videos. Of course, this transcript was created with deep learning techniques largely automatically and only minor manual modifications were performed. Try it yourself! If you […]
Read more about Lecture Notes in Pattern Recognition: Episode 2 – Pattern Recognition Postulates