From e020e6c70a71b7c3c7c02c914df5c5fb19f6f839 Mon Sep 17 00:00:00 2001
From: Sarah Pratt <sarahmhpratt75@gmail.com>
Date: Tue, 13 Feb 2024 15:17:30 -0800
Subject: [PATCH] assignment 4

---
 assignments/assignment4.html | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/assignments/assignment4.html b/assignments/assignment4.html
index c3802b2..335fde6 100644
--- a/assignments/assignment4.html
+++ b/assignments/assignment4.html
@@ -85,11 +85,12 @@ <h3 id="goals">Goals</h3>
       <ul>
         <li>Gain experience with a major deep learning framework, <strong>PyTorch</strong>.</li>
         <li>Explore various applications of image gradients, including saliency maps, fooling images, class visualizations.</li>
+        <li>Understand and implement RNN networks.</li>
       </ul>      
 
 
 <h3 id="q1-pytorch--tensorflow-on-cifar-10">Q1: PyTorch on CIFAR-10</h3>
-<p>For this last part, you will be working in PyTorch, a popular and powerful deep learning framework.
+<p>For this first part, you will be working in PyTorch, a popular and powerful deep learning framework.
 <p>Open up <code class="language-plaintext highlighter-rouge">PyTorch.ipynb</code>. There, you will learn how the framework works, culminating in training a  convolutional network of your own design on CIFAR-10 to get the best performance you can.</p> 
 
 <h3 id="q2-network-visualization-saliency-maps-class-visualization-and-fooling-images">Q2: Network Visualization: Saliency Maps, Class Visualization, and Fooling Images</h3>