Neural Networks For Your Dog - 3.2 Random Weights

3.2 Random Weights

In this lecture, we’ll introduce the formal structure of a neural network and then we’ll code one up with random weights.

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