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New posts in neural-network

How inverting the dropout compensates the effect of dropout and keeps expected values unchanged?

machine-learning neural-network deep-learning regularized dropout

Balanced Accuracy Score in Tensorflow

tensorflow machine-learning neural-network conv-neural-network metrics

How to determine for which value artificial neuron will fire?

artificial-intelligence neural-network

Neural Networks and Image Processing to Shoot Caterpillars w/ Lasers

image-processing neural-network

PyBrain: When creating network from ground up how and where do you create a bias?

python neural-network pybrain

Caffe output layer number accuracy

machine-learning computer-vision neural-network deep-learning caffe

How reconstruct the caffe net by using pycaffe

python neural-network deep-learning caffe pycaffe

caffe: model definition: write same layer with different phase using caffe.NetSpec()

neural-network deep-learning caffe

Tensor Flow - LSTM - 'Tensor' object not iterable

python neural-network tensorflow lstm

Setting the number of output nodes in scikit-learn's MLPClassifier

python scikit-learn neural-network perceptron

Neuroph Vs Encog

neural-network encog

What do node gradients represent in a neural network?

neural-network

How do I load a caffe model and convert to a numpy array?

python numpy neural-network deep-learning caffe

Keras 2 fit_generator UserWarning: `steps_per_epoch` is not the same as the Keras 1 argument `samples_per_epoch`

python neural-network keras jupyter-notebook keras-2

How does one implement adversarial examples in pytorch?

python machine-learning neural-network conv-neural-network pytorch

How to implement Merge from Keras.layers

python python-3.x neural-network keras keras-layer

How to define specific number of convolutional kernels/filters in pytorch?

python neural-network pytorch

References for data normalization

machine-learning neural-network

Simple Neural Network can't learn XOR

ruby machine-learning neural-network

neuralnet in R - Getting same output for all input values

r neural-network
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