Coding Challenge #70: Nearest Neighbors Recommendation Engine - Part 3

In this multi-part coding challenge, I create a movie recommendation engine using the "nearest neighbor" algorithm. Code: https://thecodingtrain.com/challenges/70-nearest-neighbors-recommendation-engine p5.js Web Editor Sketches: 🕹️ Nearest Neighbors, Part 1: https://editor.p5js.org/codingtrain/sketches/S2jhCLS9m 🕹️ Nearest Neighbors, Part 2: https://editor.p5js.org/codingtrain/sketches/0tBrSEhTg 🕹️ Nearest Neighbors, Part 3: https://editor.p5js.org/codingtrain/sketches/aIYPcl4me 🕹️ Nearest Neighbors, Part 3 with added styling: https://editor.p5js.org/codingtrain/sketches/-WBVNk45K Other Parts of this Challenge: 📺 Nearest Neighbors Recommendation Engine - Part 1: https://youtu.be/N8Fabn1om2k 📺 Nearest Neighbors Recommendation Engine - Part 2: https://youtu.be/Lo89NLmSgl0 🎥 Previous video: https://youtu.be/flxOkx0yLrY?list=PLRqwX-V7Uu6ZiZxtDDRCi6uhfTH4FilpH 🎥 Next video: https://youtu.be/LFU5ZlrR21E?list=PLRqwX-V7Uu6ZiZxtDDRCi6uhfTH4FilpH 🎥 All videos: https://www.youtube.com/playlist?list=PLRqwX-V7Uu6ZiZxtDDRCi6uhfTH4FilpH References: 📕 The Nature of Code Part 2 (Spring 2017) - Intelligence and Learning: https://github.com/shiffman/NOC-S17-2-Intelligence-Learning 📓 Notes on Pearson's correlation coefficient: https://github.com/shiffman/NOC-S17-2-Intelligence-Learning/wiki/Glossary:-Statistics#correlation Videos: 🚂 My Video on Associative Arrays: https://www.youtube.com/watch?v=_5jdE6RKxVk 🔴 Coding Train Live 91: https://youtu.be/Do_Gftp_oug?t=7983s Related Coding Challenges: 🚂 #98 Quadtree: https://youtu.be/OJxEcs0w_kE 🚂 #104 Linear Regression with TensorFlow.js: https://youtu.be/dLp10CFIvxI 🚂 #105 Polynomial Regression with TensorFlow.js: https://youtu.be/tIXDik5SGsI Timestamps: 0:00 Introduction 1:14 Loop through the titles 3:45 Add "not seen" option 4:20 Predict ratings 5:10 Add the drop-downs to an array 7:57 Change "not seen" to null 9:38 Change euclideanDistance() to receive user object 13:03 Format similarity score 18:06 Predict star rating 25:44 Weighted sum of similarity scores 28:20 Error checking 30:10 What could you do? 31:18 movielens Editing by Mathieu Blanchette Animations by Jason Heglund Music from Epidemic Sound 🚂 Website: http://thecodingtrain.com/ 👾 Share Your Creation! https://thecodingtrain.com/guides/passenger-showcase-guide 🚩 Suggest Topics: https://github.com/CodingTrain/Suggestion-Box 💡 GitHub: https://github.com/CodingTrain 💬 Discord: https://thecodingtrain.com/discord 💖 Membership: http://youtube.com/thecodingtrain/join 🛒 Store: https://standard.tv/codingtrain 🖋️ Twitter: https://twitter.com/thecodingtrain 📸 Instagram: https://www.instagram.com/the.coding.train/ 🎥 Coding Challenges: https://www.youtube.com/playlist?list=PLRqwX-V7Uu6ZiZxtDDRCi6uhfTH4FilpH 🎥 Intro to Programming: https://www.youtube.com/playlist?list=PLRqwX-V7Uu6Zy51Q-x9tMWIv9cueOFTFA 🔗 p5.js: https://p5js.org 🔗 p5.js Web Editor: https://editor.p5js.org/ 🔗 Processing: https://processing.org 📄 Code of Conduct: https://github.com/CodingTrain/Code-of-Conduct This description was auto-generated. If you see a problem, please open an issue: https://github.com/CodingTrain/thecodingtrain.com/issues/new #nearestneighbors #similarityscore #euclideandistance #associativearrays #p5js #javascript