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Please complete the following using Python. To implement a multi-layer feedforward back-propagation algorithm (we can just call it ANN) that can "Teach a Neural Network for Classification". Requirement: 1. You must have three layers (input, hidden, and output) in your architecture. 2. Use the Sigmoid function as your transfer function. Implement the ANN (NOT perceptron) to recognize 4 blocks image (such as the one image shown below) to make a decision if an image is BRIGHT or DARK. Remember that we have 16 samples for the input. You must have at least three layers in your ANN: input layer, hidden layer, and output layer. + If it contains 2, 3, or 4 white pixels, it is "bright" + If it contains 0 or 1 white pixels, it is "dark

          Please complete the following using Python.
To implement a multi-layer feedforward back-propagation algorithm (we can just call it ANN) that can "Teach a Neural Network for Classification". Requirement:
1. You must have three layers (input, hidden, and output) in your architecture.
2. Use the Sigmoid function as your transfer function.
Implement the ANN (NOT perceptron) to recognize 4 blocks image (such as the one image shown below) to make a decision if an image is BRIGHT or DARK. Remember that we have 16 samples for the input.
You must have at least three layers in your ANN: input layer, hidden layer, and output layer.
+ If it contains 2, 3, or 4 white pixels, it is "bright"
+ If it contains 0 or 1 white pixels, it is "dark

Added by Patrick V.

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