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 YH 提供Feb 9, 2022
The project is well designed, helpful. I learn a lot from this project. Thank you very much
由 YZ 提供Dec 21, 2021
Very detailed explanation on each step, and helped me to get a concrete idea on real world data processing using BERT
由 JS 提供Dec 14, 2020
Great course. Easy to follow & straightforward explanations.
由 DA 提供Apr 15, 2021
really nice glue to connect all the dots. Thanks so much