by Marcus Hilliard

In this work, we examined several different architectures associated with various neural networks for the classification of news articles from the AG dataset. We show through different experiments that the optimum number of word tokens varies based on the model foundations (i.e., structure of the input data). We then build and test several neural networks designed for natural language processing (NLP). We then chose the optimum model and provide recommendations for implementation.

In this work, we explore the realm of multilayer perceptrons (MLP), convolutional neural networks (CNN), recurrent neural networks (RNN), long short memory networks (LSTM), and…

Marcus Hilliard

Sometimes I create the mystery box…

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