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Model subclassing and custom training loops in Tensorflow for the Reuters dataset. Natural language processing and document classification

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Reuters dataset: Model subclassing and custom training loops

Objective: employ model subclassing and custom training loops in Tensorflow to train a model for the Reuters dataset.

Reuters is a benchmark dataset for document classification. It is a multiclass dataset, with 46 posible classes for each of the text fragments.

A similar code employing the Sequential API of Tensorflow can be foung in Kaggle: https://www.kaggle.com/drscarlat/reuters-document-classification-with-keras-tf

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Model subclassing and custom training loops in Tensorflow for the Reuters dataset. Natural language processing and document classification

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