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.
YC
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.
AT
it is very helpful and simply explain the idea of Bert model , really it is useful project
AP
This course helped me to understand the Transformer architecture and also various NLP techniques.
AA
Excellent and very helpful course, the instructor language is very clear and concise and to the point, I would love to learn more from the same instructor.
JH
I have some experience on computer vision and need to take a NLP project, this course give me a heads up on the project.
RL
Need a bit of preknowledge of bert and preprocessing
JB
Need More detail explanation as its a advance NLP topic.
YH
The project is well designed, helpful. I learn a lot from this project. Thank you very much
FY
It would be helpful if the course was also offered outside of Google colab environment (standalone).
VS
The project was well explained and provided good understanding of bert for text classification. Also the quiz were good.
JS
Great course. Easy to follow & straightforward explanations.
Showing: 20 of 41
Unable to complete the course because the version of tensorflow used in it doesn't play nice anymore with the collab environment the course use :(
1.No video are there to explain the concepts(it has a video link which doesn't work).
2.There is no Rhyme Environment as mentioned in the description.
3.It only has a notebook which contains only the code without any explanation.
Very helpful to have it explained so patiently and thoroughly. I am not sure how one starts to really be able to practically work these deep and intricate libraries without the training wheels of all the guidance in these courses. But regardless, if would probably be prohibitively difficult without them, so I am grateful fo all the folks at Coursera that take the time to produce this material and courses.
The course is just awesome. I searched a ton of tutorials on fine tuning before landing onto this guided-project and I can't tell how blessed I feel now. The course is even better than most full TensorFlow tutorials which teach all the vague stuff that I have to omit all the time. Snehan has beautifully explained what is "just necessary" to dive into fine tuning BERT.
Thanks for the course :)
This course can help us to understand BERT for text classification with tensorflow and the material presented is quite easy to follow :)
Helped me cement the basic understanding on how to use BERT for my use case.
Excellent course for those who already has done some research on the field.
Gerçekten aydınlatıcı ve anlaşılır bir eğitim. (Ben ücretsiz bu eğitime eriştim. )
Uygulamalı eğitimler her zaman teorikten daha kalıcı oluyor. Üstelik kişinin ben bunu yapabilirim deme noktasında bir özgüven verdiği de gerçek.
Eğitmenlerime ve içeriği hazırlamada yardımı dokunan herkese çok teşekkür ederim
This is such a great course !!!! The instructor prepared the knowledge very well, and he is so good at teaching ! I have learned a lot skills about Bert model in this course ! You should not miss it. I am hoping to see more course from this instructor! Thank you so much for making such a great course !
Excellent and very helpful course, the instructor language is very clear and concise and to the point, I would love to learn more from the same instructor.
I have some experience on computer vision and need to take a NLP project, this course give me a heads up on the project.
The project was well explained and provided good understanding of bert for text classification. Also the quiz were good.
It would be helpful if the course was also offered outside of Google colab environment (standalone).
This course helped me to understand the Transformer architecture and also various NLP techniques.
it is very helpful and simply explain the idea of Bert model , really it is useful project
The project is well designed, helpful. I learn a lot from this project. Thank you very much
Great course. Easy to follow & straightforward explanations.
really nice glue to connect all the dots. Thanks so much
Need More detail explanation as its a advance NLP topic.
Need a bit of preknowledge of bert and preprocessing