Getting Started with Neural Networks: Perceptrons & Neural Network Algorithms

Neural Networks    |    Intermediate
  • 10 Videos | 48m 8s
  • Includes Assessment
  • Earns a Badge
Likes 7 Likes 7
Discover the basics of perceptrons, including single- layer and multilayer, and the roles of linear and nonlinear functions in this 10-video course. Learners will explore how to implement perceptrons and perceptron classifiers by using Python for machine learning solutions. Key concepts covered in this course include perceptrons, single-layer and multilayer perceptrons, and the computational role they play in artificial neural networks; learning the algorithms that can be used to implement single-layer perceptron training models; and exploring multilayer perceptrons and illustrating the algorithmic difference from single-layer perceptrons. Next, you will learn to classify the role of linear and nonlinear functions in perceptrons; learn how to implement perceptrons by using Python; and learn approaches and benefits of using the backpropagation algorithm in neural networks. Then learn the uses of linear and nonlinear activation functions in artificial neural networks; learn to implement a simple perceptron classifier using Python; and learn the benefits of using the backpropagation algorithm in neural networks and implement perceptrons and perceptron classifiers by using Python.

WHAT YOU WILL LEARN

  • discover the key concepts covered in this course
    describe perceptrons and the computational role they play in artificial neural networks
    recognize the algorithms that can be used to implement single layer perceptron training models
    define multilayer perceptrons and illustrate the algorithmic difference from single layer perceptrons
    classify the role of linear and non-linear functions in perceptrons
  • demonstrate the implementation of perceptrons using Python
    describe approaches and benefits of using the backpropagation algorithm in neural networks
    recognize the uses of linear and non-linear activation functions in artificial neural networks
    implement a simple perceptron classifier using Python
    recall the benefits of using the backpropagation algorithm in neural networks, and implement perceptrons and perceptron classifiers using Python

IN THIS COURSE

  • Playable
    1. 
    Course Overview
    1m 23s
    UP NEXT
  • Playable
    2. 
    Perceptrons
    5m 42s
  • Locked
    3. 
    Single Layer Perceptron Training Model
    4m 45s
    FREE ACCESS
  • Locked
    4. 
    Multilayer Perceptrons
    5m 9s
    FREE ACCESS
  • Locked
    5. 
    Linear and Non-Linear Functions
    4m 52s
    FREE ACCESS
  • Locked
    6. 
    Implement Perceptrons with Python
    4m 51s
    FREE ACCESS
  • Locked
    7. 
    Backpropagation
    3m 52s
    FREE ACCESS
  • Locked
    8. 
    Activation Functions
    4m 18s
    FREE ACCESS
  • Locked
    9. 
    Perceptron Classifier
    4m 45s
    FREE ACCESS
  • Locked
    10. 
    Exercise: Implement Perceptrons
    4m 31s
    FREE ACCESS

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