<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Machine Learning | Zerui "Jerry" Ma's personal website</title><link>https://jerma88.github.io/tags/machine-learning/</link><atom:link href="https://jerma88.github.io/tags/machine-learning/index.xml" rel="self" type="application/rss+xml"/><description>Machine Learning</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Wed, 15 Jan 2025 00:00:00 +0000</lastBuildDate><image><url>https://jerma88.github.io/media/icon_hu_982c5d63a71b2961.png</url><title>Machine Learning</title><link>https://jerma88.github.io/tags/machine-learning/</link></image><item><title>Graduate Teaching Assistant (Machine Learning, Advanced Python, Digital Logic)</title><link>https://jerma88.github.io/teaching/smu-ta/</link><pubDate>Wed, 15 Jan 2025 00:00:00 +0000</pubDate><guid>https://jerma88.github.io/teaching/smu-ta/</guid><description>&lt;h1 id="graduate-teaching-assistant--southern-methodist-university">Graduate Teaching Assistant — Southern Methodist University&lt;/h1>
&lt;p>&lt;strong>Lyle School of Engineering&lt;/strong>&lt;br>
&lt;em>January 2025 – May 2026 | Dallas, TX&lt;/em>&lt;/p>
&lt;h2 id="courses-supported">Courses Supported&lt;/h2>
&lt;ul>
&lt;li>&lt;strong>Machine Learning&lt;/strong> (Undergraduate / Graduate)&lt;/li>
&lt;li>&lt;strong>Advanced Python Programming&lt;/strong>&lt;/li>
&lt;li>&lt;strong>Digital Logic Design &amp;amp; Hardware Laboratories&lt;/strong>&lt;/li>
&lt;/ul>
&lt;h2 id="key-responsibilities">Key Responsibilities&lt;/h2>
&lt;ul>
&lt;li>Instructed and mentored over &lt;strong>100+ students&lt;/strong> in fundamental and advanced Machine Learning concepts, including gradient descent optimization, loss functions, neural network architectures, and transformer attention mechanisms.&lt;/li>
&lt;li>Led weekly hands-on coding laboratories and office hours, guiding students through implementing machine learning models from scratch in Python, PyTorch, and scikit-learn.&lt;/li>
&lt;li>Designed curriculum and laboratory experiments for digital systems and VLSI testing, directing students in implementing JTAG boundary-scan controllers and debugging Verilog HDL on Xilinx FPGAs.&lt;/li>
&lt;/ul></description></item><item><title>AI &amp; Machine Learning Course Lecturer</title><link>https://jerma88.github.io/teaching/governors-camp/</link><pubDate>Mon, 01 Jul 2024 00:00:00 +0000</pubDate><guid>https://jerma88.github.io/teaching/governors-camp/</guid><description>&lt;h1 id="ai--machine-learning-course-lecturer">AI &amp;amp; Machine Learning Course Lecturer&lt;/h1>
&lt;p>&lt;strong>Governor’s Champion Summer Camp, Southern Methodist University&lt;/strong>&lt;br>
&lt;em>July 2024 | Dallas, TX&lt;/em>&lt;/p>
&lt;h2 id="course-overview">Course Overview&lt;/h2>
&lt;p>Designed and delivered a comprehensive 4-week curriculum covering artificial intelligence and modern machine learning for talented high school scholars.&lt;/p>
&lt;h2 id="topics-covered">Topics Covered&lt;/h2>
&lt;ul>
&lt;li>&lt;strong>Intelligent Agents &amp;amp; Search Algorithms&lt;/strong>: State-space search, heuristic evaluation, and graph traversal.&lt;/li>
&lt;li>&lt;strong>Data Preprocessing &amp;amp; Feature Engineering&lt;/strong>: Tabular transformations, normalization, and handling missing data with Pandas and NumPy.&lt;/li>
&lt;li>&lt;strong>Supervised Learning&lt;/strong>: Linear/logistic regression, decision trees, and classification metrics.&lt;/li>
&lt;li>&lt;strong>Deep Neural Networks&lt;/strong>: Multi-layer perceptrons, activation functions, backpropagation intuition, and introductory computer vision.&lt;/li>
&lt;li>Guided students through end-to-end hands-on capstone projects applying ML models to real-world datasets.&lt;/li>
&lt;/ul></description></item></channel></rss>