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This post discusses the self-attention algorithm.
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This post discusses the back propagation through time (BPTT).
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This post discusses the recurrent neural networks.
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This post discusses word embeddings and the methods of using word embeddings.
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This post covers tokenization and building a vector representation of a statement.
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This post shows some case studies in CNN such as LeNet-5, AlexNet, VGG, ResNet, and GoogleNet.
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This post explains the convolution layer in CNN.
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This post shows the architecture of CNN.
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This post explains the key concepts involved at Convolutional Neural Network (CNN).
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This post contains a slide deck that explains basic concepts of Machine Learning with a focus on Nueural Networks.