Fine Tune BERT for Text Classification with TensorFlow

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En este Proyecto guiado gratuito, tú:
2.5 hours
Intermedio
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Video de pantalla dividida
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This is a guided project on fine-tuning a Bidirectional Transformers for Language Understanding (BERT) model for text classification with TensorFlow. In this 2.5 hour long project, you will learn to preprocess and tokenize data for BERT classification, build TensorFlow input pipelines for text data with the tf.data API, and train and evaluate a fine-tuned BERT model for text classification with TensorFlow 2 and TensorFlow Hub. Prerequisites: In order to successfully complete this project, you should be competent in the Python programming language, be familiar with deep learning for Natural Language Processing (NLP), and have trained models with TensorFlow or and its Keras API. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Requerimientos

Habilidades que desarrollarás

  • natural-language-processing

  • Tensorflow

  • machine-learning

  • deep-learning

  • BERT

Aprende paso a paso

En un video que se reproduce en una pantalla dividida con tu área de trabajo, tu instructor te guiará en cada paso:

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Tu espacio de trabajo es un escritorio virtual directamente en tu navegador, no requiere descarga.

En un video de pantalla dividida, tu instructor te guía paso a paso

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