Neural Networks For Your Dog - 3.6 Stochastic Gradient Descent

3.6 Stochastic Gradient Descent

In this lecture, we’ll see how stochastic gradient descent can be used to improve the learning algorithm by reducing time, memory, and convergence on local minima.

Code

Course Curriculum

(See the code on GitHub)

1. Introduction
   1.1 Introduction
2. Perceptron
   2.1 MNIST Dataset
   2.2 Perceptron Model
   2.3 Perceptron Learning Algorithm
   2.4 Pocket Algorithm
   2.5 Multiclass Support
   2.6 Perceptron To Neural Network
3. Neural Network
   3.1 Simple Images
   3.2 Random Weights
   3.3 Gradient Descent
   3.4 Multiclass Support
   3.5 Deep Learning
   3.6 Stochastic Gradient Descent
   3.7 Going Further

Additional Content

1. Python NumPy For Your Grandma
2. Python Pandas For Your Grandpa
3. Introduction To Google Colab