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Tag: MNIST

Keras An implementation of a Convolutional Neural Network in Keras

# K An implementation of a Convolutional Neural Network in Keras – MNIST dataset

In this post we will see how we can classify handwritten digits using convolutional neural network implemented in Keras. Required packages: Numpy Matplotlib Keras Tensorflow Sklearn Seaborn __future__ Keras-vis Table of Contents: Load the digit dataset Implementing a Neural Network Visualization Test our model Save a model as picture Activation Maps Saliency maps Activations Now we can plot some predictions, to see how our model works. Images for testing can be downloaded from the internet…
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# K An implementation of a Shallow Neural Network in Keras – MNIST dataset

In this post we will see how we can classify handwritten digits using shallow neural network implemented in Keras. Our model will have 2 layers, with 64(height x width) neurons in the input layer and 10 neurons in the output layer.We will use normal initializer that generates tensors with a normal distribution. The optimizer we’ll use is Adam .It is an optimization algorithm that can be used instead of the classical stochastic gradient descent procedure…
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