Gradient Descent, Step-by-Step
StatQuest with Josh Starmer StatQuest with Josh Starmer
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 Published On Feb 5, 2019

Gradient Descent is the workhorse behind most of Machine Learning. When you fit a machine learning method to a training dataset, you're probably using Gradient Descent. It can optimize parameters in a wide variety of settings. Since it's so fundamental to Machine Learning, I decided to make a "step-by-step" video that shows you exactly how it works.

NOTE: This video assumes you are already familiar with Least Squares and Linear Regression. If not, here's the link to the Quest:    • The Main Ideas of Fitting a Line to D...  

For a complete index of all the StatQuest videos, check out:
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Sources:
There are a ton of websites that describe the math behind Gradient Descent. One of my favorite is the wikipedia article: https://en.wikipedia.org/wiki/Gradien...

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0:00 Awesome song and introduction
1:25 Main ideas behind Gradient Descent
5:38 Gradient Descent optimization of a single variable, part 1
9:08 An important note about why we use Gradient Descent
9:40 Gradient Descent optimization of a single variable, part 2
14:48 Review of concepts covered so far
15:48 Gradient Descent optimization of two (or more) variables
21:55 A note about Loss Functions
22:13 Gradient Descent algorithm
23:06 Stochastic Gradient Descent

#statquest #gradient #descent #ML

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