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Voltar para Fine Tune BERT for Text Classification with TensorFlow

Comentários e feedback de alunos de Fine Tune BERT for Text Classification with TensorFlow da instituição Coursera Project Network

4.5
estrelas
64 classificações
15 avaliações

Sobre o curso

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....

Melhores avaliações

VS
12 de Abr de 2021

The project was well explained and provided good understanding of bert for text classification. Also the quiz were good.

FY
13 de Mai de 2021

It would be helpful if the course was also offered outside of Google colab environment (standalone).

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1 — 15 de 15 Avaliações para o Fine Tune BERT for Text Classification with TensorFlow

por Anup P

16 de Nov de 2020

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

por David N

10 de Mar de 2021

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.

por Feng J

17 de Fev de 2021

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 !

por Vijender S

13 de Abr de 2021

The project was well explained and provided good understanding of bert for text classification. Also the quiz were good.

por Fancy Y

14 de Mai de 2021

It would be helpful if the course was also offered outside of Google colab environment (standalone).

por ABHISHEK S

5 de Abr de 2021

Helped me cement the basic understanding on how to use BERT for my use case.

por James S

15 de Dez de 2020

Great course. Easy to follow & straightforward explanations.

por Sitison

16 de Abr de 2021

really nice glue to connect all the dots. Thanks so much

por Janmejay B

7 de Out de 2020

Need More detail explanation as its a advance NLP topic.

por Tiffany T

15 de Fev de 2021

A great introduction to BERT and with TensorFlow

por Valentina F

19 de Nov de 2020

A complex topic explain in one day

por AJAY T

20 de Set de 2020

Nice

por Jorge H G G

25 de Fev de 2021

I do not recommend taking this type of course, take one and pass it, however after a few days I have tried to review the material, and my surprise is that it asks me to pay again to be able to review the material. Of course coursera gives me a small discount for having already paid it previously. It is very easy to download the videos and difficult to get hold of the material, but with ingenuity it is possible. Then I recommend uploading them to YouTube and keeping them private for when they want to consult (they avoid legal problems and can share with friends), then they can request a refund.

por bilzard

6 de Jun de 2021

It's good to learn how to implement BERT model with pyTorch.

Personally, I need more theoretical instructions about BERT and transformer.

por vibhor s

28 de Fev de 2021

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.