<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Python |</title><link>https://spencha.github.io/tags/python/</link><atom:link href="https://spencha.github.io/tags/python/index.xml" rel="self" type="application/rss+xml"/><description>Python</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Mon, 01 Dec 2025 00:00:00 +0000</lastBuildDate><image><url>https://spencha.github.io/media/icon_hu_982c5d63a71b2961.png</url><title>Python</title><link>https://spencha.github.io/tags/python/</link></image><item><title>Hidden Markov Model for Part-of-Speech Tagging Tasks</title><link>https://spencha.github.io/projects/hmm-pos-tagging/</link><pubDate>Mon, 01 Dec 2025 00:00:00 +0000</pubDate><guid>https://spencha.github.io/projects/hmm-pos-tagging/</guid><description>&lt;p&gt;Literature review and application of Hidden Markov Model methods to the Penn Treebank dataset for STATS 230: Statistical Computing Methods.&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;Tools Used:&lt;/strong&gt; Python, R&lt;/p&gt;</description></item><item><title>Predicting the Dow Jones Industrial Average with Sentiment-Enhanced LSTM Models</title><link>https://spencha.github.io/projects/lstm-stock-prediction/</link><pubDate>Mon, 01 Dec 2025 00:00:00 +0000</pubDate><guid>https://spencha.github.io/projects/lstm-stock-prediction/</guid><description>&lt;p&gt;Project demonstrating the efficacy of LSTM models in enhancing prediction of stock indexes such as the DJIA.&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;Tools Used:&lt;/strong&gt; Python, R&lt;/p&gt;</description></item><item><title>Guest Lecturer: STATS 295 - Special Topics in Machine Learning</title><link>https://spencha.github.io/teaching/stats295-winter2025/</link><pubDate>Wed, 15 Jan 2025 00:00:00 +0000</pubDate><guid>https://spencha.github.io/teaching/stats295-winter2025/</guid><description>&lt;p&gt;Delivered two guest lectures for STATS 295, a graduate-level special topics course in machine learning:&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;
&lt;p&gt;&lt;strong&gt;Handling Data in R and Python, Web Scraping&lt;/strong&gt; (January 15, 2025) — Covered data manipulation techniques across both languages and introduced web scraping methods for collecting data from online sources.&lt;/p&gt;
&lt;/li&gt;
&lt;li&gt;
&lt;p&gt;&lt;strong&gt;PyTorch Tutorial for Deep Learning&lt;/strong&gt; (February 3, 2025) — Provided a hands-on introduction to deep learning using PyTorch, covering neural network fundamentals and practical implementation.&lt;/p&gt;
&lt;/li&gt;
&lt;/ul&gt;</description></item></channel></rss>