🚀 Deploy updated DGM site (2025-09-16 15:36)

Author: blengerich

dgm-fall-2025/lectures/index.html

@@ -186,7 +186,7 @@ <h2 class="post-description"></h2>
 
 
 
-            | <a href="" target="_blank">notes</a>
+            | <a href="/dgm-fall-2025/notes/lecture-03" target="_blank">notes</a>
 
         ]
     </td>
@@ -199,7 +199,7 @@ <h2 class="post-description"></h2>
 
 </tr>
 
-<tr class="warning">
+<tr class="past">
     <th scope="row">9/15</th>
 
     <td>
@@ -228,7 +228,7 @@ <h2 class="post-description"></h2>
 
 </tr>
 
-<tr class="upcoming">
+<tr class="warning">
     <th scope="row">9/17</th>
 
     <td>

dgm-fall-2025/notes/index.html

@@ -93,6 +93,16 @@ <h2>The notes written by students and edited by instructors</h2>
 
 <ul class="post-list">
 
+  <li >
+    <p class="post-meta">September 10, 2025</p>
+    <h2>
+      <a class="post-title" href="/dgm-fall-2025/notes/lecture-03/"
+        >Lecture 03</a
+      >
+    </h2>
+    <p>Statistics / linear algebra / calculus review</p>
+  </li>
+  
   <li >
     <p class="post-meta">September 8, 2025</p>
     <h2>

dgm-fall-2025/notes/lecture-02/index.html

@@ -168,7 +168,7 @@ <h2 id="recap">Recap</h2>
 <p>Formally, a computer program is said to learn from experience $ℇ$ with respect to some task $𝒯$ and performance measure $𝒫$ if its performance at $𝒯$ as measured by $𝒫$ improves with $ℇ$.</p>
 
 <figure>
-  <img src="/assets/img/notes/lecture-02/Recap.png" alt="" />
+  <img src="../../assets/img/notes/lecture-02/Recap.png" alt="" />
 </figure>
 
 <hr />
@@ -207,7 +207,7 @@ <h2 id="machine-learning-jargon">Machine Learning Jargon</h2>
 <h2 id="history-of-machine-learning">History of Machine Learning</h2>
 
 <figure>
-  <img src="/assets/img/notes/lecture-02/lec2-1.png" alt="" />
+  <img src="../../assets/img/notes/lecture-02/lec2-1.png" alt="" />
 </figure>
 
 <ul>
@@ -221,7 +221,7 @@ <h2 id="history-of-machine-learning">History of Machine Learning</h2>
 </ul>
 
 <figure>
-  <img src="/assets/img/notes/lecture-02/lec2-2.png" alt="" />
+  <img src="../../assets/img/notes/lecture-02/lec2-2.png" alt="" />
 </figure>
 
 <hr />
@@ -230,7 +230,7 @@ <h2 id="artificial-neurons-and-perceptrons">Artificial Neurons and Perceptrons</
 <ul>
   <li>Neural model first discussed in 1943 (McCulloch &amp; Pitts).
     <figure>
-      <img src="/assets/img/notes/lecture-02/lec2-2.png" alt="" />
+      <img src="../../assets/img/notes/lecture-02/lec2-2.png" alt="" />
   </figure>
     <ul>
       <li>Mimicked neuroscience behaviors.</li>
@@ -240,7 +240,7 @@ <h2 id="artificial-neurons-and-perceptrons">Artificial Neurons and Perceptrons</
   </li>
   <li><strong>Perceptrons</strong>:
     <figure>
-      <img src="/assets/img/notes/lecture-02/lec2-3.png" alt="" />
+      <img src="../../assets/img/notes/lecture-02/lec2-3.png" alt="" />
   </figure>
     <ul>
       <li>Horizontal = input, vertical = output.</li>
@@ -298,7 +298,7 @@ <h2 id="neural-networks-as-computation-graphs">Neural networks as computation gr
 </ul>
 
 <figure>
-  <img src="/assets/img/notes/lecture-02/fig-computation-graph.png" alt="Computation graph showing input, intermediate computations, and outputs" />
+  <img src="../../assets/img/notes/lecture-02/fig-computation-graph.png" alt="Computation graph showing input, intermediate computations, and outputs" />
 </figure>
 
 <ul>
@@ -330,7 +330,7 @@ <h2 id="about-the-term-deep-learning">About the term “Deep Learning”</h2>
 <h2 id="activation-functions">Activation Functions</h2>
 
 <figure>
-  <img src="/assets/img/notes/lecture-02/lec2-7.png" alt="" />
+  <img src="../../assets/img/notes/lecture-02/lec2-7.png" alt="" />
 </figure>
 
 <ul>
@@ -344,7 +344,7 @@ <h2 id="activation-functions">Activation Functions</h2>
 <h2 id="hardware">Hardware</h2>
 
 <figure>
-  <img src="/assets/img/notes/lecture-02/lec2-8.png" alt="" />
+  <img src="../../assets/img/notes/lecture-02/lec2-8.png" alt="" />
 </figure>
 
 <ul>