Chevron Left
Back to Fine Tune BERT for Text Classification with TensorFlow

Learner Reviews & Feedback for Fine Tune BERT for Text Classification with TensorFlow by Coursera Project Network

4.5
stars
22 ratings
5 reviews

About the Course

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....

Top reviews

AA
Nov 15, 2020

Excellent course for those who already has done some research on the field.

JS
Dec 14, 2020

Great course. Easy to follow & straightforward explanations.

Filter by:

1 - 5 of 5 Reviews for Fine Tune BERT for Text Classification with TensorFlow

By Anup

Nov 16, 2020

Excellent course for those who already has done some research on the field.

By James S

Dec 15, 2020

Great course. Easy to follow & straightforward explanations.

By Janmejay B

Oct 7, 2020

Need More detail explanation as its a advance NLP topic.

By Valentina

Nov 19, 2020

A complex topic explain in one day

By AJAY T

Sep 20, 2020

Nice