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@Mahos-H Mahos-H commented Oct 19, 2024

Problem

Visualization of how backpropagation works with weights. Considering a input vector of length 2 for able to plot the input/output.

Solution

Perceptron.py shows a simple Perceptron model capable of backpropagation and how exactly the weights are updated and visualization of the same, considering 2 input nodes and 1 output nodes. Activation function is sigmoid and loss function is mean squared error.

Perceptron.py shows a simple Perceptron model capable of backpropagation and how exactly the weights are updated and visualization of the same, considering 2 input nodes and 1 output nodes. Activation function is sigmoid and loss function is mean squared error.
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