12/2/2023 0 Comments Keras sequential model![]() ![]() compile (loss = 'categorical_crossentropy', optimizer =sgd, metrics = ) Sgd = SGD (lr =lrate, momentum = 0.9, decay =decay, nesterov = False ) add (Dense (num_classes, activation = 'softmax' ) ) add (Dense ( 512, activation = 'relu', kernel_constraint =maxnorm ( 3 ) ) ) add (MaxPooling2D (pool_size = ( 2, 2 ) ) ) add (Conv2D ( 32, ( 3, 3 ), activation = 'relu', padding = 'same', kernel_constraint =maxnorm ( 3 ) ) ) add (Conv2D ( 32, ( 3, 3 ), input_shape =input_shape, padding = 'same', activation = 'relu', kernel_constraint =maxnorm ( 3 ) ) ) However, you can few the workable code from this post. So, you maybe not able to find some definition of some variables in this post. For this exploration, we crop the lines where we use to create CNN(Convolutional Neural Network) model in our previous post. ![]() Therefore, in this post we are going to explore all of them. With Keras, deep learning model are very easy to create, but there are 5 key steps you must follow. Then you should see the version of Kerasthat installed on your machine. To verify Keras go into python console and type: import keras ![]() Then you can install Keras into your machine via a command: sudo pip install keras Where TensorFlow is the recommend backend engine.
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