I’m using MLPs to forecast a time series, I implement a code that contain a mask layer to let the model skip the mask values. for instance, in my data, the time series has a lot of NaN values, I fill it by a ‘value = -999’. I don’t want to remove it, but I want the Keras masking to

# Tag: mlp

## Python argmax of dot product of weighted matrix and vector (mnist)

What does argmax mean in this context? I am following the tutorial in this colab notebook: https://colab.research.google.com/github/chokkan/deeplearningclass/blob/master/mnist.ipynb It looks like this is saying that for every record x and its truth value y, in the vectors Xtrain and Ytrain, take the max value of the dot product of the weighted matrix W and the record x. Does this mean it