From 96367207e5f7ec888f0012a0432f650265043fc5 Mon Sep 17 00:00:00 2001 From: Eric Zelikman Date: Fri, 9 Oct 2020 11:13:55 -0400 Subject: [PATCH] Created using Colaboratory --- C1W1_(Colab)_Inputs_to_a_pre_trained_GAN.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/C1W1_(Colab)_Inputs_to_a_pre_trained_GAN.ipynb b/C1W1_(Colab)_Inputs_to_a_pre_trained_GAN.ipynb index 1ab6110..42b765b 100644 --- a/C1W1_(Colab)_Inputs_to_a_pre_trained_GAN.ipynb +++ b/C1W1_(Colab)_Inputs_to_a_pre_trained_GAN.ipynb @@ -80,7 +80,7 @@ "\n", "In terms of probabilities, the classifier wants to find $p(y|x)$, or the likelihood that given an image input $x$, you want to know the probability of its class $y$ being cat, $p(y=\\text{cat}|x)$, or dog, $p(y=\\text{dog}|x)$.\n", "\n", - "The discriminator is simply a classifier with two classes: real and fake. Given an input x, the discriminator will calculate the probabilities $p(real|x)$ and $p(fake|x)$ and classify $x$. The input $x$ can be anything that you have the generator create and is not limited to images. Your GAN can be trained on videos, text, audio, etc.\n" + "The discriminator is simply a classifier with two classes: real and fake. Given an input x, the discriminator will calculate the probabilities $p(y=\\text{real}|x)$ and $p(y=\\text{fake}|x)$ and classify $x$. The input $x$ can be anything that you have the generator create and is not limited to images. Your GAN can be trained on videos, text, audio, etc.\n" ] }, {