Cosine Similarity ← Natural Language Processing ← Socratica

Video Description

𝙄𝙣𝙩𝙧𝙤𝙙𝙪𝙘𝙞𝙣𝙜 𝙎𝙤𝙘𝙧𝙖𝙩𝙞𝙘𝙖 𝘾𝙊𝙐𝙍𝙎𝙀𝙎 https://www.socratica.com/collections Cosine Similarity is a way to compare two pieces of text (docs) to see how similar they are stylistically. This is a useful technique from Natural Language Processing, a growing subfield of AI & Machine Learning. In this lesson, we review how to use the bag of words technique to turn a piece of text into a vector, then show how the 'cosine similarity' measure is a useful way to compare two docs. As a concrete application, we compare 10 different classic novels from different authors and time periods to see how well the cosine similarity measure performs. 𝙔𝙤𝙪 𝙘𝙖𝙣 𝙟𝙪𝙢𝙥 𝙩𝙤 𝙨𝙚𝙘𝙩𝙞𝙤𝙣𝙨 𝙤𝙛 𝙩𝙝𝙚 𝙫𝙞𝙙𝙚𝙤 𝙝𝙚𝙧𝙚: 0:00 Intro 0:48 Prerequisites 1:43 The Big Idea 3:39 Cosine Similarity 4:42 Example setup 5:47 The Books 6:51 Building a Feature Vector 8:56 Writing the Functions 10:08 Computing Cosine similarities 11:30 No Stop Words 12:50 Analysis 14:00 No Nouns 𝙒𝘼𝙏𝘾𝙃 𝙉𝙀𝙓𝙏: Bag of Words https://youtu.be/kLMhePA3BiY Use Mathematica for Free https://youtu.be/rGzmG1uXklM BTW—Socratica offers a pro course, 'Mathematica Essentials,' providing key concepts for mastering Wolfram products: https://www.socratica.com/courses/mathematica-essentials Thank you to our VIP Patreon Members who helped make this video possible! José Juan Francisco Castillo Rivera KW M Andrews Jim Woodworth Marcos Silveira Christopher Kemsley Eric Eccleston Jeremy Shimanek Michael Shebanow Alvin Khaled Kevin B John Krawiec Umar Khan Tracy Karin Prell — Thank you kind friends! 💜🦉 ✷✷✷ We recommend the following (affiliate links): The Wolfram Language https://amzn.to/3D4jqvz The Mythical Man Month - Essays on Software Engineering & Project Management http://amzn.to/2tYdNeP Innumeracy: Mathematical Illiteracy and Its Consequences http://amzn.to/2ri1nf7 Mindset by Carol Dweck https://amzn.to/2q9y8Nj How to Be a Great Student (our first book!) ebook: https://amzn.to/2Lh3XSP Paperback: https://amzn.to/3t5jeH3 Kindle Unlimited: https://amzn.to/3atr8TJ ✷✷✷ If you find our work at Socratica valuable, please consider becoming our Patron on Patreon! https://www.patreon.com/socratica If you would prefer to make a one-time donation, you can also use Socratica Paypal https://www.paypal.me/socratica ✷✷✷ Written & Produced by Michael Harrison & Kimberly Hatch Harrison Edited by Megi Shuke About our Instructors: Michael earned his BS in Math from Caltech, and did his graduate work in Math at UC Berkeley and University of Washington, specializing in Number Theory. A self-taught programmer, Michael taught both Math and Computer Programming at the college level. He applied this knowledge as a financial analyst (quant) and as a programmer at Google. Kimberly earned her BS in Biology and another BS in English at Caltech. She did her graduate work in Molecular Biology at Princeton, specializing in Immunology and Neurobiology. Kimberly spent 16+ years as a research scientist and a dozen years as a biology and chemistry instructor. Michael and Kimberly Harrison co-founded Socratica. Their mission? To create the education of the future. ✷✷✷ Welcome to Socratica! We make SMART videos focusing on STEM - science, math, programming. Subscribe here: http://bit.ly/SocraticaSubscribe PLAYLISTS Study Tips http://bit.ly/StudyTipsPlaylist Python programming http://bit.ly/PythonSocratica SQL programming http://bit.ly/SQL_Socratica Chemistry http://bit.ly/Chemistry_Playlist Abstract Algebra http://bit.ly/AbstractAlgebra Astronomy http://bit.ly/AstronomySocratica Biology http://bit.ly/BiologySocratica Calculus http://bit.ly/CalculusSocratica Geometry https://bit.ly/GeometrySocratica Mathematica http://bit.ly/SocraticaMathematica #cosinesimilarity #AI #naturallanguageprocessing