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Back to Transfer Learning for NLP with TensorFlow Hub

Learner Reviews & Feedback for Transfer Learning for NLP with TensorFlow Hub by Coursera Project Network

4.8
stars
49 ratings
5 reviews

About the Course

This is a hands-on project on transfer learning for natural language processing with TensorFlow and TF Hub. By the time you complete this project, you will be able to use pre-trained NLP text embedding models from TensorFlow Hub, perform transfer learning to fine-tune models on real-world data, build and evaluate multiple models for text classification with TensorFlow, and visualize model performance metrics with Tensorboard. 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....

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1 - 5 of 5 Reviews for Transfer Learning for NLP with TensorFlow Hub

By Icaro d C B

Jan 25, 2021

Good and concise course. You will learn what the course says: How to load models from Tensorhub, see how easy it is to "fine tune" to your own data and watch the results in Tensorboard.

By BOULASSEL A

Oct 6, 2020

thanks

By Janmejay B

Oct 1, 2020

Nice project ... Make a tutorial for neural style transfer with different type of GAN...

By Tuan A T

Feb 18, 2021

useful course

By Jorge H G G

Feb 25, 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.