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Learner Reviews & Feedback for Sequence Models by DeepLearning.AI

4.8
stars
25,390 ratings
2,986 reviews

About the Course

This course will teach you how to build models for natural language, audio, and other sequence data. Thanks to deep learning, sequence algorithms are working far better than just two years ago, and this is enabling numerous exciting applications in speech recognition, music synthesis, chatbots, machine translation, natural language understanding, and many others. You will: - Understand how to build and train Recurrent Neural Networks (RNNs), and commonly-used variants such as GRUs and LSTMs. - Be able to apply sequence models to natural language problems, including text synthesis. - Be able to apply sequence models to audio applications, including speech recognition and music synthesis. This is the fifth and final course of the Deep Learning Specialization. deeplearning.ai is also partnering with the NVIDIA Deep Learning Institute (DLI) in Course 5, Sequence Models, to provide a programming assignment on Machine Translation with deep learning. You will have the opportunity to build a deep learning project with cutting-edge, industry-relevant content....

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.

AM
Jun 30, 2019

The course is very good and has taught me the all the important concepts required to build a sequence model. The assignments are also very neatly and precisely designed for the real world application.

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2901 - 2925 of 2,962 Reviews for Sequence Models

By Jerry Z T

Aug 18, 2020

The learning embedding part is kindof confusing

By Abhishek S

Jun 15, 2020

Great course but has been dumbed down too much

By Yue

Apr 26, 2019

Esperaba que los ejemplos fueran de otra forma

By Jazz

Oct 10, 2019

Should add some instruction videos of Keras

By Shanger L

Jun 4, 2018

does HW created/reviewed by different ones?

By Parikshit D

May 27, 2018

The assignments are not very satisfactory..

By CLAUDIO G T

Apr 5, 2020

Not so well explained as the other courses

By Xueying L

Jul 22, 2018

Too narrow focusing on applications in NLP

By Rahul T

Aug 9, 2020

Programming exercises was very confusing.

By Ritesh R A

Feb 2, 2020

Course should have have more descriptive

By Liang Y

Feb 10, 2019

Too many errors in the assignments

By guzhenghong

Nov 17, 2020

The mathematical part is little.

By julien r

May 25, 2020

second week was hard to follow

By stdo

Sep 27, 2019

So many errors need to fix.

By ARUN M

Feb 6, 2019

very tough for beginners

By Wynne E

Mar 14, 2018

Keras is a ball-ache.

By Long Q

Mar 17, 2019

too hard

By CARLOS G G

Jul 26, 2018

good

By Debayan C

Aug 23, 2019

As a course i think this was way too fast and also way too assumptive. I wish the instructions were a bit slow and we broke down more into designing bilstms and how they work and more simple programming excercises. As a whole i think 1 full week of material is missing from this course which would concentrate on the basic RNN building for GRUs and LSTMs and then move on to applications. I usually do not review these courses and they are pretty standard but this course left me wanting and i will consult youtube and free repos to learn about it better. I did not gain confidence on my understanding. Barely scraped through the assignments after group study and consulting people who know this stuff (which defeats the purpose of this course i believe. It is to enable me with concrete understanding and ability to build these models . It shouldn't lead me to consult others and clear out doubts .)

By 象道

Sep 16, 2019

i really learned from this course some ideas on recurrent neural net, but the assignments of this course are not completely ready for learners and are full of mistakes which have existed for more than a year. those mistakes in the assignments mislead learners pretty much if they do not study some discussion threads of the forum. this course has the lowest quality among all of Dr. Andrew Ng's. before the updated versions, a learner had better have a look at the assignments discussion forum before starting the assignments.

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

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 Sergio F

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 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

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.