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 JH 提供2021年12月24日
I have some experience on computer vision and need to take a NLP project, this course give me a heads up on the project.
由 JS 提供2020年12月14日
Great course. Easy to follow & straightforward explanations.
由 YC 提供2021年6月19日
The project is very clear and easy to follow. Would suggest providing some gmail account so that we don't have to log into the colab using our own google credentials.