I guess I need to define np somewhere, but the practise code on the website I am using doesn't actually define np anywhere. > 24 Y_train = np.utils.to_categorical(y_train, n_classes)Ģ5 Y_test = np.utils.to_categorical(y_test, n_classes)Ģ6 print ("Shape after one-hot encoding:", Y_train.shape) python django pandas python-3.x list dataframe numpy dictionary string matplotlib python-2.7 pip arrays selenium django-models json regex datetime flask csv tensorflow function for-loop jupyter-notebook algorithm django-rest-framework tkinter windows loops opencv scikit-learn beautifulsoup web-scraping visual-studio-code html anaconda pycharm. NameError Traceback (most recent call last)Ģ3 print ("Shape before one-hot encoding: ", y_train.shape) Print ("Shape after one-hot encoding:", Y_train.shape)Įrror:. Y_test = np.utils.to_categorical(y_test, n_classes) Y_train = np.utils.to_categorical(y_train, n_classes) Print ("Shape before one-hot encoding: ", y_train.shape) #one-hot encoding using keras' numpy-related utilities Each image has a 'degree' of darkness within the range of 0-255 so you need to reduce that range to 0-1 for your Neural Network X_train = X_train.astype('float32') #using a 32-bit precision when training the neural network. X_train = X_train.reshape (60000, 784) #flattening the image into 28x28 pixels, so into an array of 784. #flattens the images from the 28x28 pixels to 1D 787 pixels (X_train, y_train), (X_test, y_test) = mnist.load_data()įrom keras.models import Sequential #imports the sequential modelįrom keras.layers import Dense, Dropout, Conv2D, MaxPool2D 'How to get the remainder of a number when dividing in python' 'json' is not defined 'jupyter (notebook OR lab)' ipynb 'not trusted' 'must be called with either an object pk or a slug in the URLconf' 'not equal to' python symbol 'PyGTK' python setup.py egginfo Check the logs for full command output.
I have tried to run the code below (not yet finished, I was testing it) when it comes up with an error (can be seen below the code). I am running a MNIST example in a Jupyter notebook running in an Anaconda virtual environment.
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