3.3: Linear Regression with Ordinary Least Squares Part 2 - Intelligence and Learning

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In this video, part of my series on "Machine Learning", I explain how to perform Linear Regression for a 2D dataset using the Ordinary Least Squares method. This is Part 2 where I demonstrate how to code the algorithm in JavaScript, using the p5.js library

Link to Part 1: https://youtu.be/szXbuO3bVRk

This video is part of session 3 of my Spring 2017 ITP "Intelligence and Learning" course (https://github.com/shiffman/NOC-S17-2-Intelligence-Learning/tree/master/week3-classification-regression)

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Links discussed in this video:
Session 3 of Intelligence and Learning: https://github.com/shiffman/NOC-S17-2-Intelligence-Learning/tree/master/week3-classification-regression
Nature of Code: http://natureofcode.com/
kwichmann's Linear Regression Diagnostics: https://kwichmann.github.io/ml_sandbox/linear_regression_diagnostics/
Linear Regression on Wikipedia: https://en.wikipedia.org/wiki/Linear_regression
Anscombe's quartet on Wikipedia: https://en.wikipedia.org/wiki/Anscombe%27s_quartet
My video on the p5.js map() function: https://youtu.be/nicMAoW6u1g

Source Code for the all Video Lessons: https://github.com/CodingTrain/Rainbow-Code

p5.js: https://p5js.org/
Processing: https://processing.org


For More Coding Challenges: https://www.youtube.com/playlist?list=PLRqwX-V7Uu6ZiZxtDDRCi6uhfTH4FilpH
For More Intelligence and Learning: https://www.youtube.com/playlist?list=PLRqwX-V7Uu6YJ3XfHhT2Mm4Y5I99nrIKX

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