Training Neural Networks in Python

Introduction

• Creating a neural network in Python
• What you should know
• Using GitHub Codespaces with this course

1. Choosing a Neural Network

• What is a neural network?
• Why Python
• The many applications of machine learning
• Types of classifiers
• Types of neural networks
• Multilayer perceptrons

2. The Building Blocks of Neural Networks

• Neurons and the brain
• A simple model of a neuron
• Activation functions
• Perceptrons: A better model of a neuron
• Challenge: Finish the perceptron
• Solution: Finish the perceptron
• Logic gates
• Challenge: Logic gates with perceptrons
• Solution: Logic gates with perceptrons

3. Building Your Network

• Linear separability
• Writing the multilayer perceptron class
• Challenge: Finish the multilayer perceptron class
• Solution: Finish the multilayer perceptron class

4. Training Your Network

• The need for training
• The training process
• The error function
• Gradient descent
• The Delta rule
• The Backpropagation algorithm
• Challenge: Write your own Backpropagation method
• Solution: Write your own Backpropagation method

5. Let's Make a Segment Display Classifier

• Segment display recognition
• Challenge: Design your own SDR neural network
• Solution: Design your own SDR neural network
• Challenge: Train your own SDR neural network
• Solution: Train your own SDR neural network
• 7 to 1 network GUI demo
• 7 to 10 network GUI demo
• 7 to 7 network GUI demo

Conclusion

• Next steps