Getting Started with Neural Networks: Perceptrons & Neural Network Algorithms

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.