<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Cluster | Xuanhao</title><link>https://www.xh-zhang.com/tags/cluster/</link><atom:link href="https://www.xh-zhang.com/tags/cluster/index.xml" rel="self" type="application/rss+xml"/><description>Cluster</description><generator>Source Themes Academic (https://sourcethemes.com/academic/)</generator><language>en-us</language><lastBuildDate>Thu, 01 Oct 2020 17:30:40 -0400</lastBuildDate><image><url>https://www.xh-zhang.com/img/icon-192.png</url><title>Cluster</title><link>https://www.xh-zhang.com/tags/cluster/</link></image><item><title>Movie Recommendation System</title><link>https://www.xh-zhang.com/project/movie/</link><pubDate>Thu, 01 Oct 2020 17:30:40 -0400</pubDate><guid>https://www.xh-zhang.com/project/movie/</guid><description>
&lt;h2 id=&#34;movie-recommendation-system&#34;&gt;Movie Recommendation System&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Built a movie recommendation system based on Collaborative Filter in PySpark on the MovieLens Dataset.&lt;/li&gt;
&lt;li&gt;Conducted ETL scripts to ﬁlter movies’ categories, rating or other information with Pandas and Spark.&lt;/li&gt;
&lt;li&gt;Analyzed and compared the performance with other cluster algorithms like K-means and DBSCAN.&lt;/li&gt;
&lt;/ul&gt;</description></item></channel></rss>