<feed xmlns="http://www.w3.org/2005/Atom"> <id>https://tducvu.github.io/</id><title>Fragments of a Dot</title><subtitle>A blog for Python blogging</subtitle> <updated>2022-06-07T14:01:15-07:00</updated> <author> <name>Duc Vu</name> <uri>https://tducvu.github.io/</uri> </author><link rel="self" type="application/atom+xml" href="https://tducvu.github.io/feed.xml"/><link rel="alternate" type="text/html" hreflang="en-US" href="https://tducvu.github.io/"/> <generator uri="https://jekyllrb.com/" version="4.2.2">Jekyll</generator> <rights> © 2022 Duc Vu </rights> <icon>/assets/img/favicons/favicon.ico</icon> <logo>/assets/img/favicons/favicon-96x96.png</logo> <entry><title>PIC16B-Project Reflection</title><link href="https://tducvu.github.io/posts/pic16b_project_reflection/" rel="alternate" type="text/html" title="PIC16B-Project Reflection" /><published>2021-06-09T19:01:10-07:00</published> <updated>2021-06-09T19:01:10-07:00</updated> <id>https://tducvu.github.io/posts/pic16b_project_reflection/</id> <content src="https://tducvu.github.io/posts/pic16b_project_reflection/" /> <author> <name>Duc Vu</name> </author> <category term="PIC16B-blog" /> <summary> Now that the very first offering of PIC16B at UCLA is over, let’s reflect on what we, i.e., Alice and I, had worked and achieved together for the project, which is one of the most crucial components of the class. Project Overview: Colorization has a variety of applications in recreational and historical context. It transforms how we see and perceive photos which helps us tremendously in visual... </summary> </entry> <entry><title>Classifying Fake News with TensorFlow</title><link href="https://tducvu.github.io/posts/fake_news/" rel="alternate" type="text/html" title="Classifying Fake News with TensorFlow" /><published>2021-05-24T22:05:01-07:00</published> <updated>2021-05-24T22:05:01-07:00</updated> <id>https://tducvu.github.io/posts/fake_news/</id> <content src="https://tducvu.github.io/posts/fake_news/" /> <author> <name>Duc Vu</name> </author> <category term="PIC16B-blog" /> <summary> Are you confident with your ability to spot fake news? Do you know that seven in ten Americans overestimate their ability in identifying false headlines? Well, one should even wonder whether what I just claimed is verifiable and truthful or not. Thus, instead of spending hours researching and verifying from one source to another, why we dont’t leave this task to our trustworthy computer. With t... </summary> </entry> <entry><title>Spectral Clustering</title><link href="https://tducvu.github.io/posts/spectral_clustering/" rel="alternate" type="text/html" title="Spectral Clustering" /><published>2021-04-30T18:00:00-07:00</published> <updated>2021-04-30T18:00:00-07:00</updated> <id>https://tducvu.github.io/posts/spectral_clustering/</id> <content src="https://tducvu.github.io/posts/spectral_clustering/" /> <author> <name>Duc Vu</name> </author> <category term="PIC16B-blog" /> <summary> In this blog post, we will study and create a spectral clustering algorithm which is basically used in exploratory data analysis to divide data points into different group where each group has their own characteristics/features. Notation In all the math below: Boldface capital letters like \(\mathbf{A}\) refer to matrices (2d arrays of numbers). Boldface lowercase letters like \(\mathbf... </summary> </entry> <entry><title>Data Visualization with NOAA Climate Data Set</title><link href="https://tducvu.github.io/posts/noaa_visualization/" rel="alternate" type="text/html" title="Data Visualization with NOAA Climate Data Set" /><published>2021-04-14T19:57:50-07:00</published> <updated>2021-04-14T19:57:50-07:00</updated> <id>https://tducvu.github.io/posts/noaa_visualization/</id> <content src="https://tducvu.github.io/posts/noaa_visualization/" /> <author> <name>Duc Vu</name> </author> <category term="PIC16B-blog" /> <summary> In this assignment, we will be working with the NOAA climate data set to create some interesting visualizations. \(\S 1.\) Database There are three tables that we need to create within a database which are stations, countries, and temperatures. In order to generate a database, we need the help from sqlite3 which is a module that allows us to conveniently create and query databases. import sql... </summary> </entry> <entry><title>Feature Selection Through Visualization</title><link href="https://tducvu.github.io/posts/feature_selection/" rel="alternate" type="text/html" title="Feature Selection Through Visualization" /><published>2021-03-22T23:50:59-07:00</published> <updated>2021-03-22T23:50:59-07:00</updated> <id>https://tducvu.github.io/posts/feature_selection/</id> <content src="https://tducvu.github.io/posts/feature_selection/" /> <author> <name>Duc Vu</name> </author> <category term="PIC16B-blog" /> <summary> In this very first post of PIC16B, I will demonstrate how to visualize the Palmer Penguins data set with the help of panda and seaborn which is a data visualization library based on matplotlib. Data Preparation First, we need to load the data set using read_csv() function from panda. import pandas as pd url = "https://raw.githubusercontent.com/PhilChodrow/PIC16B/master/datasets/palmer_penguin... </summary> </entry> </feed>
