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Learner Reviews & Feedback for Sequence Models by DeepLearning.AI

4.8
stars
25,463 ratings
2,996 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

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.

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.

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2826 - 2850 of 2,969 Reviews for Sequence Models

By Touqeer A

Aug 9, 2020

Assignments in this course are relatively less organized. You have to read a lot of description first and then code and have to go back/forth between code and description.

By Daniel E

Jul 12, 2018

I believe that the course needs more time allocated to the incremental teaching of this rather large subject area with varied applications. Just needs to be a better way.

By Loic R W

Sep 26, 2019

The course was especially interesting in week 2 and 3, but the assignments for week 1 were confusing and sometimes it was hard to follow where the logic was coming from.

By Aditya D

Aug 24, 2020

This was the most difficult to understand course in the whole specialization. Would have enjoyed more if the course material was a little more spaced and elaborated on.

By Navid A

Aug 27, 2020

The first week is amazing. The last week is the worst! Andrew starts nicely; but as he goes to the second and third weeks, he hardly explains why he does what he does.

By Дмитрий П

Apr 9, 2018

Practical Assignments with Keras wasn't motivating. I spend more time to deep into the Keras rather than into the course topic. I prefer them to be using TF or Python.

By 许晶鑫

Jun 11, 2018

The supports in keras programming was so poor, that I could not quite understand each step. And the server was horrible, always got 405 response when saving my codes.

By Joseph G B

Jun 9, 2020

This course should be broken into 4 weeks and spend more time building skills with Keras. The number of hours listed next to each assignment is unrealistically low.

By 赵凌乔

Sep 20, 2019

The lecture was great but the errors in the programming assignment (especially in formal-typed formulas) really wasted a lot of time and make me confusing at first.

By Sebastian S

Mar 14, 2019

The ideas presented here were clear, however I found the programming assignments non-intuitive and not practical. I spent on them way more time than I wish i had.

By Fernando A G

Jul 27, 2018

I enjoyed all the courses, from my personal point of view this course was not that fun as the other courses. Except for the trigger assignment it was awesome!

By Zhao H

Jul 6, 2018

Too much was given in external python code for the first week's assignment (that should be learnt by us): not a good thing for us to gain a good understanding

By Matias A

Aug 11, 2020

Worst course of the specialization, content is interesting and Andrew keeps explaining really well but programming assignments are clearly of a lower quality

By Max W

Sep 7, 2018

The course is great but the tasks in Keras are too complex without background knowledge. Therefore, a reasonable introduction in Keras would be desirable.

By Eymard P

Jul 31, 2018

Far less detailed than the other ones. The programming assignements are less interesting too, as a great part of the work consist of reading documentation

By Reetu H

Dec 23, 2019

There were lot of bugs in the assignments taking up lot of time to fix. The course was okay, I liked the other courses in the specialization more.

By Kaupo V

May 7, 2018

The Keras programming exercises are quite weak. Please re-think how to teach them more systematically. Currently it is quite a lot of hit and miss.

By Leandro A

Mar 18, 2018

There was a bug in a programming assignment notebook that took too much time to notice that i was doing ok but the expected ouptut was wrong

By David H P

Apr 2, 2018

The programming assignments required some extra effort to understand Keras which I thought may need an introduction video like tensorflow.

By Iván V P

Feb 18, 2018

Several grader issues, only 3 weeks of work, and a lot of errors in the solutions... In addition, less content than in the other courses...

By Rishabh G

Sep 19, 2020

The earlier courses were easy to understand, however, this was way too difficult. Andrew Ng did not make this easy like the other courses.

By Hang Y

Aug 24, 2018

Compared with previous courses, this one seems to be rushed. The focus on applications seems to be much higher than the theoretic side.

By Yash R S

May 9, 2018

Not as great as the other courses in the specialisation. The assignments can be a little off putting, but lectures are top class again.

By Roberto S

May 12, 2020

Week 1 took double time to be completed. Times proposed for the assingnement are underestimated.

Please readjust the assingement time.

By Ankit S

Jul 17, 2018

Assignments are not up t the mark.. Expected to have high vocabulary size word embedding assignment, Machine Translation assignments