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<!DOCTYPE html>
<html lang="en">
<head>
<!-- Meta Information -->
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1">
<meta name="author" content="Yue Zhao">
<meta name="description" content="Course website of CSCI 566 AT USC">
<meta name="keywords" content="machine learning, data mining, csci566, usc, Yue Zhao">
<!-- Title and Favicon -->
<title>CSCI 566 Deep Learning and its Applications</title>
<link rel="icon" type="image/x-icon" href="images/logo2.ico">
<!-- Stylesheets -->
<link rel="stylesheet" href="https://unpkg.com/bootstrap@5.3.0/dist/css/bootstrap.min.css" crossorigin="anonymous">
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.0.0-beta3/css/all.min.css">
<link href="https://fonts.googleapis.com/css2?family=Roboto:wght@400;700&display=swap" rel="stylesheet">
<link href="https://fonts.googleapis.com/css2?family=Poppins:wght@700&display=swap" rel="stylesheet">
<!-- Scripts -->
<script src="https://unpkg.com/bootstrap@5.3.0/dist/js/bootstrap.bundle.min.js" crossorigin="anonymous"></script>
</head>
<body>
<style>
body {
font-family: 'Roboto', '-apple-system', 'BlinkMacSystemFont', 'Segoe UI', 'Helvetica Neue', 'Arial', 'Noto Sans', 'sans-serif', 'Apple Color Emoji', 'Segoe UI Emoji', 'Segoe UI Symbol', 'Noto Color Emoji';
}
/* Global Styles */
h1, h2, h3 {
text-align: center;
}
.university-color {
color: #990000;
}
.link-list a {
margin-right: 5px;
}
/* Staff Container Styles */
.staff-container {
display: flex;
justify-content: space-between;
align-items: center;
flex-wrap: wrap;
margin: 20px;
}
.staff-member {
width: 23%;
text-align: center;
margin: 15px 1%;
box-sizing: border-box;
}
.staff-member img {
width: 80%;
max-width: 150px;
height: auto;
border-radius: 50%;
margin-bottom: 10px;
}
.staff-member h2, .staff-member p {
margin: 5px 0;
}
/* Responsive Styles */
@media only screen and (max-width: 1024px) {
.staff-member {
width: 48%;
margin: 15px 1%;
}
.staff-member img {
width: 70%;
max-width: 130px;
}
}
@media only screen and (max-width: 768px) {
.staff-member {
width: 100%;
margin: 15px 0;
}
.staff-member img {
width: 60%;
max-width: 120px;
}
</style>
<!-- Navigation -->
<nav class="navbar navbar-expand-lg navbar-dark bg-dark mb-4">
<div class="container">
<!-- Navbar header -->
<a class="navbar-brand" href="#">CSCI 566 Deep Learning and its Applications</a>
<button class="navbar-toggler" type="button" data-toggle="collapse" data-target="#navbarNav" aria-controls="navbarNav" aria-expanded="false" aria-label="Toggle navigation">
<span class="navbar-toggler-icon"></span>
</button>
<!-- Navbar links -->
<div class="collapse navbar-collapse" id="navbarNav">
<ul class="navbar-nav custom-spacing">
<li class="nav-item"><a class="nav-link" href="index.html">Home</a></li>
<li class="nav-item"><a class="nav-link" href="schedule.html">Course Schedule</a></li>
<li class="nav-item"><a class="nav-link" href="https://docs.google.com/document/d/1VpVCXoxE-CHsywkA6jeLqI6WIx2C9NsqXnDJ5EoMoGc/edit?usp=sharing">Syllabus (USC login required)</a></li>
</ul>
</div>
</div>
</nav>
<div class="container">
<h2>Schedule</h2>
<p><strong class="university-color">The schedule is subject to change
</strong>: The course website is still <strong>under construction</strong>; please check back frequently.
</p>
<div class="table-responsive">
<table class="table table-bordered">
<thead>
<tr>
<th>Date</th>
<th>Lecture</th>
<th>Homework / Readings</th>
<th>Logistics</th>
</tr>
</thead>
<tbody>
<td colspan="4" style="text-align:center;"><strong>Module 1: ML and DL Foundations</strong></td>
</tr>
<tr>
<td><strong>Week 1</strong><br>Jan 17</td>
<td>
1. Course Introduction<br>
2. My Research Overview: AI Robustness and Trustworthiness<br>
3. My Research Overview: AI4Science and ML Systems<br>
4. Framing ML Problems<br>
5. ML as Function Approximation<br>
6. Linear Models<br>
7. Job or Ph.D.? Is it a Question.
</td>
<td></td>
<td><a href="https://drive.google.com/file/d/1cjOm5IKcDF8U-_bAF_wuWQncPTLTK82A/view?usp=sharing" target="_blank">Lecture Note 1</a></td>
</tr>
<tr>
<td><strong>Week 2</strong><br>Jan 24</td>
<td>
1. Project idea discussion<br>
2. Classical ML<br>
- Decision Trees and Ensembles; tree of thoughts in LLMs<br>
- k-Nearest Neighbors; kNN-LLMs<br>
- Clustering (with LLMs) <br>
- Anomaly Detection <br>
3. Cloud computing service tutorial<br>
</td>
<td></td>
<td><a href="https://drive.google.com/file/d/1Yd3OYcyJDYjwZzIQdQ-IhtI3292lL13h/view?usp=sharing" target="_blank">Lecture Note 2</a></td>
</tr>
<tr>
<td><strong>Week 3</strong><br>Jan 31</td>
<td>
1. Classical ML (continued)<br>
Neural Network Basics<br>
- Perceptron Revisited <br>
- Gradient Descent <br>
- Forward Propagation <br>
- Activations in LLMs <br>
- Finetuning LLMs without backpropagation via hypertuning
2. Project idea discussion<br>
</td>
<td></td>
<td><a href="https://drive.google.com/file/d/1u27YCk1VEZh81Y-Ka6OxxA5EOMCs3uZ_/view?usp=sharing" target="_blank">Lecture Note 3</a></td>
</tr>
<tr>
<td><strong>Week 4</strong><br>Feb 7</td>
<td>
1. Neural Network Basics<br>
- Backpropagation <br>
- Vanishing Gradient <br>
2. Different types of Neural Networks:<br>
- Convolutional Neural Networks<br>
<br>
<span style="color:blue;"><em>Guest Lecture: Nikos Kanakaris (USC) - How to design effective prompts with large models for real-world applications</em></span><br>
<a href="https://www.linkedin.com/in/nkanak/" target="_blank" style="color:purple;">Nikos Kanakaris</a>
</td>
<td>Quiz 1</td>
<td>Course Project Teams Formed; Pre-proposal DUE<br></td>
</tr>
<tr>
<td><strong>Week 5</strong><br>Feb 14</td>
<td>
1. Different types of Neural Networks:<br>
- Convolutional Neural Networks<br>
2. Deep Learning Software Tutorial (maybe)<br>
</td>
<td>Assignment 1 OUT</td>
<td></td>
</tr>
<tr>
<td><strong>Week 6</strong><br>Feb 21</td>
<td>
<strong>Different types of Neural Networks:</strong><br>
1. Recurrent Neural Networks (RNN) & LSTM<br>
2. Graph Neural Networks (GNN)<br>
<span style="color:blue;"><em>Guest Lecture: Maria Shaukat (LinkedIn) - Responsible AI & AI/ML Career Opportunities</em></span><br>
<a href="https://www.linkedin.com/in/maria-shaukat/" style="color:purple;">Maria Shaukat</a>
</td>
<td></td>
<td></td>
</tr>
<tr>
<td><strong>Week 7</strong><br>Feb 28</td>
<td>
<strong>Automated ML and Transfer Learning</strong><br>
<span style="color:blue;"><em>Guest Discussion (TBD)</em></span>
</td>
<td></td>
<td></td>
</tr>
<tr>
<tr>
<td><strong>Week 8</strong><br><span style="color:red;">Mar 7</span></td>
<td>
<strong style="color:red;">MIDTERM EXAM</strong>
<span style="color:red;"><em>(in class, paper-based, open book but no electronics)</em></span>
</td>
<td></td>
<td></td>
</tr>
<tr>
<td><strong>Week 9</strong><br><span style="color:blue;">Mar 14</span></td>
<td>
<strong>Training dynamics</strong><br>
<span style="color:purple;"><em>Guest Discussion (TBD)</em></span>
</td>
<td><span style="color:blue;">Assignment 2 OUT</span></td>
<td><span style="color:green;">Assignment 1 DUE</span></td>
</tr>
<tr>
<td><strong>Week 10</strong><br>Mar 21</td>
<td>NO CLASS; Spring Recess</td>
<td></td>
<td></td>
</tr>
<td colspan="4" style="text-align:center;"><strong>Module 2: Deep Learning Applications & Advanced Topics</strong></td>
</tr>
<tr>
<td><strong>Week 11</strong><br>Mar 28</td>
<td>
<strong>Generative AI</strong><br>
1. Generative adversarial networks (GAN)<br>
2. Variational AutoEncoder (VAE)<br>
3. Case Study on Controllable Text Generation<br>
<span style="color:blue;"><em>Guest Lecture: Prof. Yang Shi (Utah State) - DL in Education</em></span>
<br>
<a href="https://sites.google.com/site/yshicv/" target="_blank" style="color:purple;">Prof. Yang Shi's Website</a>
</td>
<td>Quiz 2</td>
<td></td>
</tr>
<tr>
<td><strong>Week 12</strong><br>Apr 4</td>
<td>
<strong>Attention, Relation, and Memory Networks</strong><br>
<!-- <span style="color:blue;"><em>Guest Discussion (TBD)</em></span>-->
</td>
<td></td>
<td>Assignment 2 DUE</td>
</tr>
<tr>
<td><strong>Week 13</strong><br>Apr 11</td>
<td>
<strong>Contrastive Learning and Self-supervised Learning</strong><br>
<span style="color:blue;"><em>Guest Discussion (TBD)</em></span>
</td>
<td>Assignment 3 OUT</td>
<td></td>
</tr>
<tr>
<td><strong>Week 14</strong><br>Apr 18</td>
<td>
<strong>Reinforcement Learning</strong><br>
<!-- <span style="color:blue;"><em>Guest Discussion (TBD)</em></span>-->
</td>
<td></td>
<td></td>
</tr>
<tr>
<td><strong>Week 15</strong><br>Apr 25</td>
<td>Team Project Presentations (zoom; TBA)</td>
<td></td>
<td></td>
</tr>
<tr>
<td><strong>Week 16</strong><br>May 2</td>
<td>Team Project Presentations (in person)</td>
<td></td>
<td>Assignment 3 DUE</td>
</tr>
<tr>
<td><strong>Final Report</strong></td>
<td>Final Report Due on University Final Exam Day</td>
<td>(No in-class Exam)</td>
<td>Final Project Report DUE on gradescope</td>
</tr>
</tbody>
</table>
</div>
</div>
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<p style="font-family: 'Oswald', sans-serif; font-size: 15px; color: #555;">© Copyright 2024 University of Southern California.</p>
<p style="font-family: 'Oswald', sans-serif; font-size: 15px; color: #555;">Written by Yue Zhao and ChatGPT from scratch! <a href="https://github.com/USC-ASAP/CICS566-S24" target="_blank" style="color: #888; text-decoration: none;">Reuse our code</a>.</p>
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