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WebMar 20, 2024 · If we go back to our notebook with the MNIST data set, we can then define our neural net, an optimizer and the loss function. net = SimpleNeuralNet(28*28,100,10) optimizer = optim.SGD(net.parameters(),lr=1e-1) criterion = F.nll_loss. And after this we can call this function to find our learning rate and plot the results. WebSimply copy and paste your dataset into the calculator. Learn more about the principles of outlier detection and exactly how this test works in the description below the calculator. 1. Choose significance level. Alpha = 0.05 (standard) Alpha = 0.01. 2. Enter or paste your data. black box employment

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