From the course: Artificial Intelligence Foundations: Neural Networks
Join today to access over 24,900 courses taught by industry experts.
Artificial neural networks
From the course: Artificial Intelligence Foundations: Neural Networks
Artificial neural networks
- [Presenter] An artificial neuron is a mathematical function where each neuron takes inputs, weighs them separately, sums them up, and passes to some through a non-linear function to produce output. When we say non-linear, think of its opposite which is linear or a straight line. So non-linear will not be a straight line through a set of data points. Here is an example of a linear model where we have the number of personnel versus employee cost, and a non-linear model, which is population growth over time. All neurons have three basic functions, receive signals or information, integrate incoming signals to determine whether or not the information should be passed along, and communicate signals to target cells, which are other neurons or muscles or glands. The artificial neuron has the following characteristics. One or more inputs are separately weighted. Inputs are summed and passed through a non-linear function to…
Download courses and learn on the go
Watch courses on your mobile device without an internet connection. Download courses using your iOS or Android LinkedIn Learning app.