Fine Tune BERT for Text Classification with TensorFlow
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.
由 RL 提供2021年8月7日
Need a bit of preknowledge of bert and preprocessing
由 DA 提供2021年4月15日
really nice glue to connect all the dots. Thanks so much
由 FY 提供2021年5月13日
It would be helpful if the course was also offered outside of Google colab environment (standalone).
由 VS 提供2021年4月12日
The project was well explained and provided good understanding of bert for text classification. Also the quiz were good.