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Learner Reviews & Feedback for Natural Language Processing with Attention Models by DeepLearning.AI

4.4
stars
968 ratings

About the Course

In Course 4 of the Natural Language Processing Specialization, you will: a) Translate complete English sentences into German using an encoder-decoder attention model, b) Build a Transformer model to summarize text, c) Use T5 and BERT models to perform question-answering, and d) Build a chatbot using a Reformer model. By the end of this Specialization, you will have designed NLP applications that perform question-answering and sentiment analysis, created tools to translate languages and summarize text, and even built a chatbot! Learners should have a working knowledge of machine learning, intermediate Python including experience with a deep learning framework (e.g., TensorFlow, Keras), as well as proficiency in calculus, linear algebra, and statistics. Please make sure that you’ve completed course 3 - Natural Language Processing with Sequence Models - before starting this course. This Specialization is designed and taught by two experts in NLP, machine learning, and deep learning. Younes Bensouda Mourri is an Instructor of AI at Stanford University who also helped build the Deep Learning Specialization. Łukasz Kaiser is a Staff Research Scientist at Google Brain and the co-author of Tensorflow, the Tensor2Tensor and Trax libraries, and the Transformer paper....

Top reviews

JH

Oct 4, 2020

Can the instructors make maybe a video explaining the ungraded lab? That will be useful. Other students find it difficult to understand both LSH attention layer ungraded lab. Thanks

SB

Nov 20, 2020

The course is a very comprehensive one and covers all state-of-the-art techniques used in NLP. It's quite an advanced level course and a good python coding skill is a must.

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76 - 100 of 237 Reviews for Natural Language Processing with Attention Models

By Patrick A

Nov 26, 2020

An excellent course that covers research that was published about two months early.

It doen't get more cutting edge than that, and the technology (reversible residual layers) is immediately applicable and a very powerful enabler.

Thanks a lot!

By vadim m

Oct 17, 2020

An amazing level of breadth and depth of the material presented. State of the art techniques are exemplified via carefully crafted lab assignments with sufficient hints for students to be able to comprehend hard technical concepts.

By Jim F

Feb 28, 2021

Thanks for setting out to do the impossible and creating this set of courses. You have opened a doorway to understanding where the state of the art is. The rest is up to me. That's the purpose of education.

By Simin F

Nov 27, 2020

Helpful and Interesting! This course leads me gradually understand how transformer works and being optimized along with several models without much confusions. Great thanks for the deeplearning.ai Team!!

By lonnie

Jun 23, 2021

This course is briliant which talks about SOTA models such as Transformer, BERT. It would be better to have a Capstone Project. And entire projects can be downloaded easily.

By Adrien B

Apr 12, 2021

Quite complete course on the (current) state of the art of NLP. Interesting assigment using Trax. Some good introduction about big NLP model like GPT/T5/BERT.

By Aleksander M

Oct 13, 2020

Great course! I really enjoyed extensive non-graded notebooks on LSH attention. Some content was pretty challenging, but always very rewarding!

Thank you!

By Фирсанова В И

Apr 26, 2021

The course was very informative, I gained several new skills and find a lot of new, and now I feel myself much more confident in NLP, thank you!

By 西川 尚之

Oct 18, 2020

Thanks Lukasz Kaiser and Younes Mourri ,Trax and coursera team!

This NLP specialization is most imporrtant and useful i've ever been before!

By SANG Đ N

Apr 10, 2023

This is a very useful course for learning attention technique. Teacher explained very clearly. Assignments were really exciting.

By Ehsan G

Mar 5, 2023

Very well-designed and organized. Instructors are excelent. Some slides could be better; it would be great if that were fixed.

By Divyansh S

Apr 29, 2023

The course is so great you should definitely check it out it will give you deep insight through Natural language processing.

By wei z

Dec 28, 2023

This NLP specialization is very well designed. I refreshed my AL learning at school years ago, and learned new things here.

By Nicolas F V D

Sep 23, 2021

It's a great way to get started with state-of-the-art NLP techniques, following the recommended papers is extremely useful.

By Dmitri

Dec 20, 2020

Great course! I understood a lot of things and got a valuable experience working with the state-of-the-art architectures 👍

By Umberto S

Apr 17, 2021

Really practical course. It seems the SOTA in NLP, touching Transformers, BERT, T5, Reformers. So I think it's worth it

By Olawale S

Mar 18, 2024

I would give this class 6 stars if possible. Topics were well explained and, at a good pace. Thanks to the team @DLAI

By Ovidio M M

Apr 17, 2021

This is a very recommendable course to understand state-of-the-art NLP techniques and models using neural networks.

By Shahin Z

Oct 27, 2020

Everything was great.

Slides & notebooks/exercise were amazing

The content is superb and very up-to-date.

By Ruiliang L

May 31, 2021

The course is good. If we download powerpoint and files in jupyter notebook, that will be great.

By Ajay G

Jul 21, 2021

Nice course to get the details of Attention with latest state of the art deep learning models.

By Martin P

Mar 22, 2021

Great course with great lecturers. Lecturers have clearly showed how far NLP research is.

By Syed M F R

Oct 11, 2020

Loved the last week of the course, stood out amongst the other 15 of the specialization.

By Snehasish S

Aug 24, 2023

Very Good course to understand the concept of transformer model and transfer learning

By Bhupi D

Oct 19, 2020

Critical to keep abreast of state of art models in NLP and new frameworks like Trax.