From 59291fd8e0866c60114854e0f88919a7b0e48e13 Mon Sep 17 00:00:00 2001 From: Lloyd Jones Date: Tue, 21 Apr 2020 09:54:57 +0100 Subject: [PATCH] Update 14_resnet.ipynb Typo fix --- 14_resnet.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/14_resnet.ipynb b/14_resnet.ipynb index c58774e..d0e80dc 100644 --- a/14_resnet.ipynb +++ b/14_resnet.ipynb @@ -32,7 +32,7 @@ "source": [ "In this chapter, we will build on top of the CNNs (Convolutional Neural Networks) introduced in the previous chapter and explain to you the ResNet (for residual network) architecture. It was introduced in 2015 in [this article](https://arxiv.org/abs/1512.03385) and is by far the most used model architecture nowadays. More recent developments in image models almost always use the same trick of residual connections, and most of the time, they are just a tweak of the original ResNet.\n", "\n", - "We will first show you the basic ResNet as it was first designed, then explain to you what modern tweaks make it more performamt. But first, we will need a problem a little bit more difficult than the MNIST dataset, since we are already close to 100% accuracy with a regular CNN on it." + "We will first show you the basic ResNet as it was first designed, then explain to you what modern tweaks make it more performant. But first, we will need a problem a little bit more difficult than the MNIST dataset, since we are already close to 100% accuracy with a regular CNN on it." ] }, {