Implement a Multilayer Perceptron network in python that accepts different topol

Question

Implement a Multilayer Perceptron network in python that accepts different topologies and learning rate. The network topology must be specified by a vector where the first and the last element represents numbers of inputs and outputs respectively. In Figure 1 and shown an example of Neural Network in the format [2,3,2,1] where the network has two inputs, three neurons in the first layer, two Neurons on the second layer and one on the first layer. Evaluate the result using Absolute (Mean Absolute Error - MAE). The apparent error MAE (training set is used for testing) must be less than 1000. This value represents a net neural errors in average 1000 USD the price cars ranging between 5000 and 35 000 USD.THE CODE MUST FUNCTION FOR AND,XOR,OR
Implement a Multilayer Perceptron network in python that accepts different topologies and learning rate. The network topology must be specified by a vector where the first and the last element represents numbers of inputs and outputs respectively. In Figure 1 and shown an example of Neural Network in the format [2,3,2,1] where the network has two inputs, three neurons in the first layer, two Neurons on the second layer and one on the first layer. Evaluate the result using Absolute (Mean Absolute Error - MAE). The apparent error MAE (training set is used for testing) must be less than 1000. This value represents a net neural errors in average 1000 USD the price cars ranging between 5000 and 35 000 USD.THE CODE MUST FUNCTION FOR AND,XOR,OR
Evaluate the result using Absolute (Mean Absolute Error - MAE). The apparent error MAE (training set is used for testing) must be less than 1000. This value represents a net neural errors in average 1000 USD the price cars ranging between 5000 and 35 000 USD.THE CODE MUST FUNCTION FOR AND,XOR,OR

Explanation / Answer

https://gist.github.com/amueller/2061456

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