Training Neural Networks in Python
Offered By: LinkedIn Learning
Course Description
Overview
Take a deep dive into the inner workings of neural networks by learning how to create one from scratch in Python.
Syllabus
Introduction
- Creating a neural network in Python
- What you should know
- Using GitHub Codespaces with this course
- What is a neural network?
- Why Python
- The many applications of machine learning
- Types of classifiers
- Types of neural networks
- Multilayer perceptrons
- 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
- Linear separability
- Writing the multilayer perceptron class
- Challenge: Finish the multilayer perceptron class
- Solution: Finish the multilayer perceptron class
- 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
- 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
- Next steps
Taught by
Eduardo CorpeƱo
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