EPISODE · Jun 16, 2017 · 11 MIN
Intro - The Math of Intelligence
from Siraj Raval
Welcome to The Math of Intelligence! In this 3 month course, we'll cover the most fundamental math concepts in Machine Learning. In this first lesson, we'll go over a very popular optimization technique called gradient descent to help us predict how many calories a cyclist would burn given just their distance traveled. We'll also follow the story of 2 data scientists as they attempt to find the Higgs-Boson (God particle) via anomaly detection. No collaborations, this is an independent course. Code for this video (with challenge details): https://github.com/llSourcell/Intro_to_the_Math_of_intelligence TypicalHog's winning code: https://github.com/TypicalHog/THCrypt Syllabus for this course: https://github.com/llSourcell/The_Math_of_Intelligence Please Subscribe! And like. And comment. That's what keeps me going. More learning resources: http://machinelearningmastery.com/linear-regression-tutorial-using-gradient-descent-for-machine-learning/ https://spin.atomicobject.com/2014/06/24/gradient-descent-linear-regression/ https://www.coursera.org/learn/machine-learning/lecture/kCvQc/gradient-descent-for-linear-regression http://cs229.stanford.edu/notes/cs229-notes1.pdf http://blog.hackerearth.com/gradient-descent-algorithm-linear-regression https://www.r-bloggers.com/linear-regression-by-gradient-descent/ https://www.youtube.com/watch?v=XdM6ER7zTLk&t=1650s Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ And please support me on Patreon: https://www.patreon.com/user?u=3191693 Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/
What this episode covers
Welcome to The Math of Intelligence! In this 3 month course, we'll cover the most fundamental math concepts in Machine Learning. In this first lesson, we'll go over a very popular optimization technique called gradient descent to help us predict how many calories a cyclist would burn given just their distance traveled. We'll also follow the story of 2 data scientists as they attempt to find the Higgs-Boson (God particle) via anomaly detection. No collaborations, this is an independent course. Code for this video (with challenge details): https://github.com/llSourcell/Intro_to_the_Math_of_intelligence TypicalHog's winning code: https://github.com/TypicalHog/THCrypt Syllabus for this course: https://github.com/llSourcell/The_Math_of_Intelligence Please Subscribe! And like. And comment. That's what keeps me going. More learning resources: http://machinelearningmastery.com/linear-regression-tutorial-using-gradient-descent-for-machine-learning/ https://spin.atomicobject.com/2014/06/24/gradient-descent-linear-regression/ https://www.coursera.org/learn/machine-learning/lecture/kCvQc/gradient-descent-for-linear-regression http://cs229.stanford.edu/notes/cs229-notes1.pdf http://blog.hackerearth.com/gradient-descent-algorithm-linear-regression https://www.r-bloggers.com/linear-regression-by-gradient-descent/ https://www.youtube.com/watch?v=XdM6ER7zTLk&t=1650s Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ And please support me on Patreon: https://www.patreon.com/user?u=3191693 Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/
NOW PLAYING
Intro - The Math of Intelligence
No transcript for this episode yet