expected transcription loss | lecture 73 (part 3) | applied deep learning
Published 3 years ago • 625 plays • Length 14:36Download video MP4
Download video MP3
Similar videos
-
10:31
speech recognition | lecture 73 (part 1) | applied deep learning
-
5:20
cbam | lecture 8 (part 3) | applied deep learning (supplementary)
-
11:56
mobilenetv3 | lecture 16 (part 3) | applied deep learning (supplementary)
-
5:41
focal loss: a better alternative for cross-entropy
-
37:16:41
deep learning for computer vision with python and tensorflow – complete course
-
58:12
mit introduction to deep learning (2023) | 6.s191
-
12:22
focal loss | lecture 40 (part 1) | applied deep learning
-
8:40
gumbel-softmax | lecture 63 (part 3) | applied deep learning (supplementary)
-
6:30
inception-v4 | lecture 10 (part 3) | applied deep learning
-
8:55
inflated 3d convnet (i3d) | lecture 41 (part 3) | applied deep learning
-
12:01
visual question answering | lecture 63 (part 3) | applied deep learning
-
8:38
conditional gans | lecture 64 (part 3) | applied deep learning
-
12:31
multi-column dnns | lecture 3 (part 2) | applied deep learning (supplementary)
-
10:02
fréchet inception distance (fid) | lecture 69 (part 3) | applied deep learning
-
26:54
introduction to cnns | lecture 2 (part 3) | applied deep learning (supplementary)
-
14:05
fast localized spectral filtering | lecture 85 (part 2) | applied deep learning
-
7:00
beit | lecture 80 (part 2) | applied deep learning (supplementary)
-
5:45
neural network in 5 minutes | what is a neural network? | how neural networks work | simplilearn
-
0:50
layer normalization by hand
-
0:19
how to confuse a machine learning engineer