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Learner Reviews & Feedback for Sequence Models by DeepLearning.AI

4.8
stars
30,390 ratings

About the Course

In the fifth course of the Deep Learning Specialization, you will become familiar with sequence models and their exciting applications such as speech recognition, music synthesis, chatbots, machine translation, natural language processing (NLP), and more. By the end, you will be able to build and train Recurrent Neural Networks (RNNs) and commonly-used variants such as GRUs and LSTMs; apply RNNs to Character-level Language Modeling; gain experience with natural language processing and Word Embeddings; and use HuggingFace tokenizers and transformer models to solve different NLP tasks such as NER and Question Answering. The Deep Learning Specialization is a foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to take the definitive step in the world of AI by helping you gain the knowledge and skills to level up your career....

Top reviews

JY

Oct 29, 2018

The lectures covers lots of SOTA deep learning algorithms and the lectures are well-designed and easy to understand. The programming assignment is really good to enhance the understanding of lectures.

MK

Mar 13, 2024

Cant express how thankful I am to Andrew Ng, literally thought me from start to finish when my school didnt touch about it, learn a lot and decided to use my knowledge and apply to real world projects

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3201 - 3225 of 3,693 Reviews for Sequence Models

By Toma T

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Nov 15, 2023

Good course. The lesson on transformer needs to get better, be more logical with more explanations.

By Jessica

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Aug 24, 2020

Some concepts need to be explained more detailed, otherwise I feel hard to keep up with the lecture

By Zhao C

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Apr 19, 2019

Great class. However, they are some typos/mistakes in the explanations of programming assignments.

By Amiya M

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Oct 21, 2018

learned a lot but I wish their should be some sort of referencing material for further exploration

By Patrick B

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Nov 8, 2024

Lectures were very insightful. Assignments were not as strong. Final week on XFormers was rushed.

By Alex R

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Feb 25, 2019

Lecture content is pretty good. Exercises are much more finicky (less robust) than prior courses.

By MD Q A

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Apr 9, 2018

more excercise should be there in last course, but overall content was very good

thanks Andrew ng

By Sooraj M S

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May 13, 2018

The Attention model still needs more explanation. I haven't completely grasped attention models

By Jon-pierre H

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Feb 27, 2018

More errors than most in the projects. Likely due to the rush of getting this final course out

By Lee H H J

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Jun 13, 2020

Very good course, informative and easy to follow. Only problem I had is with its auto grader.

By Nojus D

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Jul 12, 2020

Really good course but compared to others optional assigments lack instructions in this one.

By Alex F

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Apr 7, 2019

My only complain is Keras. A crash course/lecture on Keras would benefit this course a lot!

By Phuong-Khanh H

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Aug 22, 2018

The course is of high quality. However, it is not as good and clear as the previous courses.

By Wes H

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Apr 15, 2018

Content needs a few improvements in quality but otherwise a valuable and instructive course.

By harm l

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Feb 19, 2018

Fine training, had some tchnicalities with the pythonn notebook which cost me loads of time.

By wayne t

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Aug 3, 2021

very good course for beginner to study. But not enough clear for some concepts and models.

By Osvaldo R

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Jul 1, 2020

The practice was more guided than other courses. Felt that the Coursera team did all for me

By Cze H Y

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Aug 16, 2018

Perfect course except there are are some mistake/ambiguous instruction in course assignment

By Tshepiso M

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Apr 5, 2020

Great course. Would like it if he kept his notation consistent with what is in the papers.

By Sven S

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Aug 9, 2019

a lot to learn, content is well presented as usual. one of the assignments requires rework

By 朱涧江

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Mar 20, 2018

Seem like not as good as before course,Wait so much time but is not clear as course before

By Yuping Y

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Mar 15, 2023

good course. Especially good in explaining the reasons and thoughts behind the algorithms

By Sarang P

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Nov 17, 2020

Trigger word detection assignment notebook has some bugs. Had a hard time submitting it

By Glorian Y

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Oct 30, 2019

There are many bugs in the assignment. Else, the material content and videos are great!

By Ryan B

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Mar 19, 2019

Really good but I guess you should teach more about how to apply all these models more.