<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>cnn on Tom Roth</title><link>https://tomroth.dev/tags/cnn/</link><description>Recent content in cnn on Tom Roth</description><generator>Hugo -- gohugo.io</generator><language>en</language><lastBuildDate>Wed, 14 Apr 2021 00:00:00 +0000</lastBuildDate><atom:link href="https://tomroth.dev/tags/cnn/index.xml" rel="self" type="application/rss+xml"/><item><title>A simple CNN with Pytorch</title><link>https://tomroth.dev/pytorch-cnn/</link><pubDate>Wed, 14 Apr 2021 00:00:00 +0000</pubDate><guid>https://tomroth.dev/pytorch-cnn/</guid><description>Find the code for this blog post here: https://github.com/puzzler10/simple_pytorch_cnn
We will build a classifier on CIFAR10 to predict the class of each image, using PyTorch along the way.
This is basically following along with the official Pytorch tutorial except I add rough notes to explain things as I go. There were a lot of things I didn&amp;rsquo;t find straightforward, so hopefully this piece can help someone else out there. If you&amp;rsquo;re reading this, I recommend having both this article and the Pytorch tutorial open.</description></item></channel></rss>