Configure the neural network playground to use the 'Spiral' dataset with 'Tanh' activation and 'L2' regularization at a rate of 0.003. Enable 'X1', 'X2', 'X1^2', and 'X2^2' features. Build a network with 3 hidden layers, setting their neuron counts to 5, 4, and 3 respectively. Run the network and report the final test and training loss after 1000 epochs.
Navigate to the Neural Network Playground URL with the networkShape parameter set to achieve 3 hidden layers with 5, 4, and 3 neurons (e.g., playground.tensorflow.org/#activation=tanh&regularization=L2&regularizationRate=0.003&dataset=spiral&neuronDecay=0.999&seed=0.5&showTestData=true&discretize=false&percTrainData=50&batchSize=10&regDataset=false&problem=classification&initZero=false&hideText=false&playButton=false&stepButton=false&resetButton=false&numHiddenLayers=3&networkShape=5,4,3&topologicalShuffle=false&x=true&y=true&xTimesY=true&xSquared=true&ySquared=true&cos=false&sin=false&dataset=spiral). Ensure the 'Spiral' dataset is selected. Verify 'Tanh' activation is selected. Verify 'L2' regularization is selected with a rate of '0.003'. Confirm that 'X1', 'X2', 'X1^2', and 'X2^2' features are enabled. Verify the network displays '3 Hidden layers' with neuron counts of 5, 4, and 3 respectively. Click the 'Run/Pause' button (id: 14) to start the network. Monitor the 'Epoch' counter and wait until it reaches at least 1000. Record the final 'Test loss' and 'Training loss' values displayed.
The 'Spiral' dataset is selected. The 'Activation' function is 'Tanh'. The 'Regularization' is 'L2' and 'Regularization rate' is '0.003'. Only 'X1', 'X2', 'X1^2', and 'X2^2' features are enabled. The network displays '3 Hidden layers'. The first hidden layer shows 5 neurons. The second hidden layer shows 4 neurons. The third hidden layer shows 3 neurons. The network runs for at least 1000 epochs. State the final 'Test loss' and 'Training loss' values observed after 1000 epochs.