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Add TensorFlow/Keras Neural Networks for Classification #11572
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# Conflicts: # machine_learning/neural_networks/cnn_mnist.py # machine_learning/neural_networks/fully_connected_mnist.py
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done
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Good
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done
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Sorry, but we can't accept this PR because it's a how-to. Your PR just uses imports all of the necessary NN functionality from TF. This repo is for educational purposes, and as such you need to provide your own implementation of your proposed algorithms. You did not implement the NNs yourself, and simply using TF to develop your models doesn't teach readers how a NN is actually implemented. This was all stated in this repo's contributing guidelines, which you indicated that you have read:
As stated in the contributing guidelines:
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Describe your change:
fully_connected_mnist.py
demonstrates a basic fully-connected feed-forward network with two hidden layers, ReLU activation, and dropout for regularization.cnn_mnist.py
implements a Convolutional Neural Network (CNN) with multiple convolutional, pooling, and batch normalization layers for feature extraction and down-sampling, followed by fully connected layers for classification.Checklist: