Domain > 10brink.github.io

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DNS Resolutions

Date	IP Address
2018-04-22	151.101.1.147 (ClassC)
2018-04-22	151.101.129.147 (ClassC)
2018-04-22	151.101.193.147 (ClassC)
2018-04-22	151.101.65.147 (ClassC)
2025-04-07	185.199.110.153 (ClassC)
2025-04-24	185.199.111.153 (ClassC)
2025-07-25	185.199.109.153 (ClassC)
2025-10-31	185.199.108.153 (ClassC)

HTTP/1.1 200 OKConnection: keep-aliveContent-Length: 7770Server: GitHub.comContent-Type: text/html; charsetutf-8permissions-policy: interest-cohort()Last-Modified: Mon, 25 Jun 2018 06:18:28 GMTAccess-

!DOCTYPE html>html langen>  head>  meta charsetUTF-8>  meta nameviewport contentwidthdevice-width, initial-scale1.0>  title>          Nick TenBrink · New Adventures in Data Science      /title>  link relstylesheet href/styles.css>  link relapple-touch-icon-precomposed sizes144x144 href/public/apple-touch-icon-precomposed.png>  link relshortcut icon href/public/favicon.ico>  link relalternate typeapplication/atom+xml titleNick TenBrink href/atom.xml>/head>  body>    div classcontainer content>      header classmasthead>        h3 classmasthead-title>          a href/ titleHome>Nick TenBrink/a>          small>New Adventures in Data Science:/small>br>                                 small>a href/about>About/a>/small>                                 small>a href/archive>Archive/a>/small>                                 small>a href/index.html>Feed/a>/small>                  /h3>      /header>      main>      div classposts>    article classpost>    h1 classpost-title>      a href/2018/06/19/SCNLP/>        Using Natural Language Processing to Topic Model Supreme Court Cases      /a>    /h1>    time datetime2018-06-19T00:00:00+00:00 classpost-date>19 Jun 2018/time>    p>The Supreme Court is the highest court in the United States. The nine justices decide which cases to hear and make judgements on. I used Natural Language Processing and unsupervised learning to preform topic modeling on the Supreme Courtcases/opinions./p>p>The tools I used were NLTK, sklearn and spacey, as well as beautiful soup for webscraping. I scraped the sitehttps://caselaw.findlaw.com/court/us-supreme-court/ to get all the opinions over the history of the US supreme court (23,000 case documents!). My original intent was to find which supreme court justices were most similar to each other, but my model mainly just picked out the various topics that they wrote about (for example fourth amendment cases, sixth amendment cases, labor laws, etc.) so I pivoted my focus to do topic modeling on the variou

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