update schedule

index.html

@@ -114,7 +114,7 @@ <h2>CSCI 566 Deep Learning and its Applications Spring 2024 <a href="mailto:usc.
                 <p><strong class="university-color">Prerequisites</strong>:
                     (1) Proficiency in Python
                     (2) College Calculus, Linear Algebra, Probability and Statistics
-                    (3) (Recommended but not required) Equivalent knowledge of <a href="https://vatsalsharan.github.io/fall22.html">CSCI 567 (Machine Learning)</a>
+                    (3) (Recommended but not required) Equivalent knowledge of <a href="https://vatsalsharan.github.io/spring24.html">CSCI 567 (Machine Learning)</a>
                 </p>
                 <p><strong class="university-color">Basic logistics</strong>:</p>
                 <ul>

schedule.html

@@ -133,12 +133,12 @@ <h2>Schedule</h2>
                         <tr>
                             <td><strong>Week 2</strong><br>Jan 19</td>
                             <td>
-                                1. Classical ML<br>
+                                Classical ML<br>
                                 &nbsp;&nbsp; - Decision Trees and Ensembles<br>
                                 &nbsp;&nbsp; - k-Nearest Neighbors<br>
                                 &nbsp;&nbsp; - Clustering <br>
                                 &nbsp;&nbsp; - Anomaly Detection <br>
-                                <em>Guest Discussion: Life in Data Science Startup (still finalizing)</em>
+<!--                                <em>Guest Discussion: Life in Data Science Startup (still finalizing)</em>-->
                             </td>
                             <td></td>
                             <td><a href="https://drive.google.com/file/d/1BX6YxF0Ezi4qfSAQ38dF6kTNOtlfnVqC/view?usp=sharing">S24-block2-classical-ML.pdf</a></td>
@@ -206,6 +206,7 @@ <h2>Schedule</h2>
                                 1. Transformers and AutoDiff<br>
                                 2. Deep Generative Models<br>
                                 3. Deep Reinforcement Learning
+                                <em>Guest Discussion: Open-source Development (Dr. Haifeng Jin @ Google)</em>
                             </td>
                             <td></td>
                             <td>Assignment 1 DUE</td>