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Learner Reviews & Feedback for Sequence Models by DeepLearning.AI

4.8
stars
30,443 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

WK

Mar 13, 2018

I was really happy because I could learn deep learning from Andrew Ng.

The lectures were fantastic and amazing.

I was able to catch really important concepts of sequence models.

Thanks a lot!

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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3651 - 3675 of 3,705 Reviews for Sequence Models

By daniele r

•

Jul 15, 2019

The subject is fascinating, the instructor is undoubtly competent, but there is a strong feeling of lower quality with respect to the other 4 courses in the Spec (in particular the first 3). Many things in this course are only hinted to, without many details. Man things are just said but not really explained. Many recording errors as well. Maybe another week could have helped in having a little more depth in the subject

By Amir M

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Sep 2, 2018

Although the course lectures are great, as are all the lectures in this specialization, some of the assignments have rough edges that need to be smoothed out. It is particularly frustrating for those trying to work on the optional/ungraded programming assignment sections that have some incorrect comparison values, as much time will be wasted trying to figure out the source of the error.

By David S

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Dec 19, 2020

Excellent lectures, terrible exercise material. E.g. "You're implementing how to train a model! But we've done the actual training for you already! Your exercise is to add numbers A and B! Number A is 4. Number B is 11! Enter A + B in the box below!" Also, someone did a search-and-replace and converted every sentence into an individual bullet point to reduce readability.

By Sergio F

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May 16, 2019

Unfortunately, this course is the less valuable in the specialization. Programming assignment very interesting but no introduction to Keras. To pass the assignments, forum support has been vital. I also found lectures not clear even to the point that to catch some concepts you have to google around for more resources. Unfortunately, I could not suggest this course.

By Guruprasad K

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Mar 9, 2022

Compared to the other courses in the specialization, this appears to lack depth and clarity one could expect. LSTMs and GRUs are somewhat out-dated now, given the speed of innovation in the field, and Transformers are here to stay (for now). Unfortunately, Transformers are very poorly covered.

By Peter B

•

Feb 20, 2018

Getting the input parameters correct for the Keras assignments is on par with the satisfaction of dropping a ring, contact lens, or an expensive object into the sink, and spending an hour looking for it inside the disassembled pipes, through built up hair debris and molded dirt.

By SARAVANAN N

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Mar 19, 2018

Overall a great course, thanks to Andrew NG for his great explanations. But a very bad support, I faced many issues in submitting the assignment due to technical issues (notebook not saving) but no dedicated resource to help me. I spend lot of time in resolving my self.

By Sergei S

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May 18, 2019

Feels again like authors tried to put everything into just a couple of weeks, thus the course turned out to be messy with lots of details hidden. Even though there was a lot to learn, I am still not sure if I understand correctly how to build a simple sequence model.

By Clement A

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Aug 7, 2020

Really good to understand the basics, however, it doesn't use the latest TF2 and the exercises are either trivial because too much pre-worked, or too hard because it doesn't give the information required to succeed.

This course really needs to be updated.

By Mladen M

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Jul 9, 2020

Programming assignment instructions are not well written (clear), and as a result it is easy to get stuck on something of little relevance to deep learning. Also, I would suggest that you make the lecture notes in written format available.

By Teo T

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Jan 3, 2023

Assigments are pretty bad. I think in CNN and in RNN we should focus more on fundementals and build everything in numpy. RNN course isnt for building intuintion(deep knowledge) you just scratch surface.

By Chris M

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Aug 21, 2019

The lectures cover the basic design of the models but don't help teaching you how to actually use them. I learned more by reading blogs to get the programming assignments to work then this course.

By Ashley H

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Sep 14, 2018

Lectures/Videos were excellent, the assignments were very poor (loads of errors in the code not corrected over 7 months since the course went live)

By yuvaraj

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Dec 11, 2020

The course videos were very lengthy and difficult to follow. Many topics discussed in course video were not part of programming assignment

By Simeon S

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Mar 18, 2020

Good introduction to the concepts. Really poor quality videos and exercises. Very frustrating when working on the assignments.

By Wijnand v W

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Oct 14, 2022

The videos were very helpful but the programming assignments were way too easy for this certificate to be worth much.

By David L

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Jun 28, 2020

Good lectures. Programming assignments are useless fill-in-the-blank exercises, you don't really learn much from them.

By XD

•

Nov 28, 2022

5 stars for lecture videos. -1 star for the terrible transformer programming assignment which is simply frustrating.

By Thomas A

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Oct 10, 2019

The programming assignments really are like pulling teeth. There's not really enough guidance leading up to them.

By Mark

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Oct 24, 2018

The course videos and the programming assignments were lacking. And there was no support in the forums.

By Jeffrey S

•

Jun 2, 2018

Spent more time trying to work around a buggy grader than learning the underlying concepts.

By ZHANPENG T

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Oct 23, 2019

Too hard to understand compared to the previous coursed in this specification.

By Dipesh K

•

Aug 13, 2022

Tough to comprehend. A little bit of written explanation might have helped.

By Hamid A

•

Nov 13, 2020

Was very difficult. please add more expiation of mathematical equations.

By Sukeesh

•

Apr 18, 2020

Little unsatisfied with the final part of the specialization.