Neural Networks For Your Dog - 3.5 Deep Learning

3.5 Deep Learning

In this lecture, we’ll see how we can generalize our neural network model to support multiple hidden layers (i.e. deep learning) and why doing so is helpful.

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