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Gradient Descent, Step-by-Step

StatQuest

Josh Starmer

Gradient Descent

Machine Learning

Statistics

Data Science

Optimization

Автор: StatQuest with Josh Starmer

Загружено: 5 февр. 2019 г.

Просмотров: 1 558 301 просмотр

Описание:

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...  

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...

For a complete index of all the StatQuest videos, check out:
https://statquest.org/video-index/

If you'd like to support StatQuest, please consider...

Patreon:   / statquest  
...or...
YouTube Membership:    / @statquest  

...buying one of my books, a study guide, a t-shirt or hoodie, or a song from the StatQuest store...
https://statquest.org/statquest-store/

...or just donating to StatQuest!
https://www.paypal.me/statquest

Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter:
  / joshuastarmer  

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

Gradient Descent, Step-by-Step

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