Golang Perceptron implementation

Play

go run cmd/sample/main.go

Perceptron prediction: 1 | Expected: 1 | Inputs: [0 0] | Weights: [0 0] | Bias: 0 | Error: 0 | Iteration: 0 | Learning Rate: 1 | Activation Function: step | Loss Function: MSE | Cost Function: MSE | Gradient Descent: batch | Backpropagation: backpropagation 
Perceptron prediction: 1 | Expected: 1 | Inputs: [0 1] | Weights: [0 0] | Bias: 0 | Error: 0 | Iteration: 1 | Learning Rate: 1 | Activation Function: step | Loss Function: MSE | Cost Function: MSE | Gradient Descent: batch | Backpropagation: backpropagation 
Perceptron prediction: 1 | Expected: 1 | Inputs: [1 0] | Weights: [0 0] | Bias: 0 | Error: 0 | Iteration: 2 | Learning Rate: 1 | Activation Function: step | Loss Function: MSE | Cost Function: MSE | Gradient Descent: batch | Backpropagation: backpropagation 
Perceptron prediction: 1 | Expected: 1 | Inputs: [1 1] | Weights: [0 0] | Bias: 0 | Error: 0 | Iteration: 3 | Learning Rate: 1 | Activation Function: step | Loss Function: MSE | Cost Function: MSE | Gradient Descent: batch | Backpropagation: backpropagation 

References

• Perceptron
• Perceptron Learning Algorithm
• Perceptron Learning Rule