From the course: Artificial Intelligence Foundations: Neural Networks

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Single-layer perceptron

Single-layer perceptron

From the course: Artificial Intelligence Foundations: Neural Networks

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Single-layer perceptron

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- [Instructor] Let's look at a high level overview of single layer perceptrons. A single layer perceptron is a type of neuron having multiple inputs and one output. Input nodes are connected to a node in the next layer. The node in the next layer takes the weighted sum of all its inputs. It is called a single layer because it has one layer that contains one computational node. A computational node is just a place where computation happens, similar to a neuron in the human brain, which fires when it encounters sufficient information signals. Shown here is our certification exam question, this time with an additional variable, hours of sleep. Here, the artificial neuron accepts input data, the hours of sleep and the hours of study, and passes the data on to another artificial neuron. Here, we have replaced our hours of sleep and hours of study with the features, X1 and X2. Our X1 and X2 input data are fed forward into…

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