Why does Keras give validation accuracies with way more decimal places than realistically needed?

I’m working with the MNIST handwritten digit dataset. It has 60k images for the training set and 10k images for the validation set. I get the validation accuracy like this: history = model.fit(trainX, trainY, epochs=10, batch_size=32, validation_data=(testX, testY)) val_accuracy = history.history[‘val_accuracy’] So how is it possible that I’m getting values like 0.9999666810035706? 1) There are…

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Programs are grouped with the program that launched them. How can I change that?

This morning, I launched Slack from the program list. Once it was up and running, I clicked a link therein, which launched Firefox. In fact, it launched four Firefox windows, each with many tabs, because Firefox remembers my previous session, and I’m disorganized like that. However, in the program switcher (Alt+Tab), the Firefox windows are…

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