Covers: theory of Gradient Descent
Why this is worth your time
easy explanation of gradient descent from Andrew Ng
How to use this item?

Watch the whole video

Fail to play? Open the link directly:
0 comment

Stochastic Gradient Descent

Total time needed: ~2 hours
Learn the basic of stochastic gradient descent as an optimizer
Potential Use Cases
Stochastic Gradient Descent (SGD) is a simple yet very efficient approach to fitting linear classifiers and regressors under convex loss functions
Who is This For ?
Click on each of the following annotated items to see details.
VIDEO 1. Stochastic gradient descent
CPSC 340 UBC ML course : lecture on Stochastic Gradient Descent (SGD)
50 minutes
VIDEO 2. Stochastic Gradient Descent
Easy explanation of SGD from Andrew Ng
12 minutes
ARTICLE 3. Toward data science - SGD
easy explanation of SGD
15 minutes
LIBRARY 4. SGD in Scikit-Learn
SGD library in scikit​-learn package in python
10 minutes
VIDEO 5. Gradient Descent with Andrew Ng
easy explanation of gradient descent from Andrew Ng
10 minutes
ARTICLE 6. Stochastic model
explanation of the ​stochastic model
10 minutes

Concepts Covered

0 comment