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學生對 提供的 Sequence Models 的評價和反饋

22,802 個評分
2,630 條評論


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. 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....



Mar 14, 2018

I was really happy because I could learn deep learning from Andrew Ng.\n\nThe lectures were fantastic and amazing.\n\nI was able to catch really important concepts of sequence models.\n\nThanks a lot!


Oct 30, 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.


2401 - Sequence Models 的 2425 個評論(共 2,612 個)

創建者 shuieryin

Feb 08, 2018

soooo difficult...

創建者 sunlight

Jul 13, 2018


創建者 Aditya M

Jun 25, 2020

Very good course

創建者 Pragyan P

Aug 11, 2018

It was tough :)

創建者 Vincenzo P

Apr 13, 2018

Very usefull!!!

創建者 guggilla s

Mar 09, 2019

easy to learn

創建者 Sayon S

Jun 11, 2018

A bit cryptic

創建者 Shephard M

Mar 28, 2018

Good material

創建者 yanhang

Jul 18, 2019

very useful

創建者 Paul A B

Feb 24, 2019

a bit hard!


Jan 31, 2019

Very Useful


Apr 18, 2020


創建者 Roberto J

Feb 14, 2018

Thank you.

創建者 Ariel H

Oct 13, 2018



Jun 01, 2020


創建者 KiranKumar B

Apr 05, 2020



Oct 24, 2019


創建者 Shashank V M

Sep 16, 2019


創建者 Yashwanth M

Jul 23, 2019


創建者 Rahila T

Nov 15, 2018


創建者 savinay

Apr 09, 2018


創建者 krishna m s g

Mar 22, 2018




創建者 Aaradhya S

Apr 25, 2020


創建者 Natalia O

Oct 04, 2019

in comparison to the previous courses from this sequence, this one is even less structured - ptobably this is because even broader knowledge is tried to be shown in only 3 weeks, but i feel like a lot is skipped between videos (which are ok) and the tasks - in many assignment tasks in this course it is not very well explained what is meant to be done - i mean this especially in case of Keras objects. In many cases it is quite unclear how those classes are supposed to be handled in the context of our task. There are some hints but those are mostly links to documentation (btw, some of the links are no longer up to date), but it is often not too well explained which properties those objects have, what one can do etc. so one ends up with trying using those objects in different configuarations, then googling around, looking on the course forum for the right answer but it is very difficult to derive it. There should be more precise instructions regarding handling Keras objects - the examples in the documentation and in blogs are often much simpler than those from assignments so one ends up not knowing what is going on. In summary - there is a big jump and a big gap between the intuitions in videos (which btw are much more fuzzy than those in first cources in the specialization, the intuitions get more and more superfluous as one doesnt go into detail) and what is being done in the assignments. One thing i really liked about hte previous assignments was that when writing the code one could really know very well what is going on. And this is no longer the case in this course...

創建者 Mark S

Oct 09, 2019

As we head to the last course in the specialization (and the last two courses are the ones that interested me), we have error after error in the assignments, including problems with the kernel that are not obvious until you've struggled with incoherent stack trace output for a while.

Searching the disorganised discussion centre for the course/week in question you can find that these errors affect everyone and go back for a couple of years, never having been fixed. The mentors there help explain, but mentors cannot edit to fix the code as they do not have permission, and the course supervisors have long since disappeared. So you have to submit incorrect code to pass, then fix the code for your personal private code store - as the fixed code generates the correct numerical answers that unfortunately do not match the numerical answers that the grader requires to pass you!

It feels like, in the hurry to get the full specialization out, the final courses go downhill in terms of care & attention in the rush. Then afterwards, all of the errors and badly designed code in the assignments cause many unexpected headaches, nothing to do with DL, and were never fixed or maintained afterwards by the course supervisors.

In the end, the delays caused to me in the final (two) course(s) added at least one extra monthly payment on to my subscription. Overall I can't complain, the specialization is good. But feels abandoned by the lecturer & assistant lecturers since early 2018