Deep Learning is an area of machine learning whose goal is to learn complex functions using special neural network architectures that are "deep" (consist of many layers).
In this is tutorial code from TensorFlow website, could anyone help explain what does global_step mean? I found on …
tensorflow deep-learningDrop-Out is regularization techniques. And I want to apply it to notMNIST data to reduce over-fitting to finish my Udacity …
neural-network tensorflow deep-learningIn Keras, we can return the output of model.fit to a history as follows: history = model.fit(X_train, …
python machine-learning neural-network deep-learning kerasBy using pyTorch there is two ways to dropout torch.nn.Dropout and torch.nn.functional.Dropout. I struggle to …
neural-network deep-learning pytorch dropoutIf we have 10 eigenvectors then we can have 10 neural nodes in input layer.If we have 5 output classes then we …
machine-learning neural-network deep-learning perceptronI am trying to train my model which classifies images. The problem I have is, they have different sizes. how …
deep-learningI'm using Lasagne to create a CNN for the MNIST dataset. I'm following closely to this example: Convolutional Neural Networks …
neural-network deep-learning conv-neural-network lasagne nolearnI would like to access the layer size of all the layers in a Sequential Keras model. My code: model = …
python tensorflow deep-learning keras theanoI try to understand LSTMs and how to build them with Keras. I found out, that there are principally the 4 …
machine-learning neural-network deep-learning keras recurrent-neural-networkI get this error : sum() got an unexpected keyword argument 'out' when I run this code: import pandas as pd, …
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