unit 4.1 | logistic regression for multiple classes | part 5 | the cross entropy loss function
Published 1 year ago • 613 plays • Length 6:33Download video MP4
Download video MP3
Similar videos
-
7:19
unit 4.1 | logistic regression for multiple classes | part 4 | cross entropy loss function
-
6:56
unit 4.1 | logistic regression for multiple classes | part 1 | the softmax regression model
-
5:48
unit 4.1 | logistic regression for multiple classes | part 2 | the softmax activation function
-
2:28
unit 4.1 | logistic regression for multiple classes | part 3 | from softmax scores to class labels
-
4:13
cross entropy (deep dive equation and intuitive understanding)
-
10:08
training softmax classifier (c2w3l09)
-
19:20
multinomial logistic regression with one dichotomous and one continuous predictor variable
-
18:43
dive into deep learning - lecture 4: logistic/softmax regression and cross entropy loss with pytorch
-
8:17
unit 3.1 | using logistic regression for classification | part 3 | the logistic regression loss
-
52:38
5- multiclass classification and cross-entropy error function
-
4:07
unit 4.5 | multilayer neural networks for regression | part 1 | architecture and loss function
-
9:31
neural networks part 6: cross entropy