Voltar para Fine Tune BERT for Text Classification with TensorFlow
Comentários e feedback de alunos de Fine Tune BERT for Text Classification with TensorFlow da instituição Coursera Project Network
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Sobre o curso
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.
Melhores avaliações
15 de Nov de 2020
Excellent course for those who already has done some research on the field.
6 de Out de 2020
Need More detail explanation as its a advance NLP topic.
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1 — 4 de 4 Avaliações para o Fine Tune BERT for Text Classification with TensorFlow
por Anup
•16 de Nov de 2020
Excellent course for those who already has done some research on the field.
por Janmejay B
•7 de Out de 2020
Need More detail explanation as its a advance NLP topic.
por Valentina
•19 de Nov de 2020
A complex topic explain in one day
por AJAY T
•20 de Set de 2020
Nice
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