Use Keras to create a neural network with two inputs, 3 hidden layers with two hidden neurons and two output neurons. Ad
Posted: Thu May 05, 2022 1:17 pm
Use Keras to create a neural network with two inputs, 3 hidden
layers with two hidden neurons and two output neurons.
Additionally, the hidden and output neurons will include a bias.
All the activation functions in hidden and output neurons are
sigmoid functions. Input and output neurons values are shown in
below: input is: [0.05, 0.1], output is: [0.01, 0.99].
(1) Generate the same 1000 samples of input [0.05, 0.1]
and output [0.01, 0.99] as your training data
(2) Loss function use MSE in the code
(3) Optimizer use adam in the code
(4) Set epochs=10, batch_size=1, shuffle=True in the code
(5) Fix random seed for reproducibility
(6) Plot training loss curve in the jupyterNotbook code
layers with two hidden neurons and two output neurons.
Additionally, the hidden and output neurons will include a bias.
All the activation functions in hidden and output neurons are
sigmoid functions. Input and output neurons values are shown in
below: input is: [0.05, 0.1], output is: [0.01, 0.99].
(1) Generate the same 1000 samples of input [0.05, 0.1]
and output [0.01, 0.99] as your training data
(2) Loss function use MSE in the code
(3) Optimizer use adam in the code
(4) Set epochs=10, batch_size=1, shuffle=True in the code
(5) Fix random seed for reproducibility
(6) Plot training loss curve in the jupyterNotbook code