dropout

PyTorch: dividing dataset, transformations, training on GPU and metric visualization

In machine learning designing the structure of the model and training the neural network are relatively small elements of a longer chain of activities. We usually start with understanding business requirements, collecting and curating data, dividing it into training, validation and test subsets, and finally serving data to the model. Along the way, there are …

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Convolutional neural network 3: convnets and overfitting

Convolutional neural network is one of the most effective neural network architecture in the field of image classification. In the first part of the tutorial, we discussed the convolution operation and built a simple densely connected neural network, which we used to classify CIFAR-10 dataset, achieving accuracy of 47%. In the second part of the …

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