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Comentários e feedback de alunos de Sequence Models da instituição deeplearning.ai

4.8
17,771 classificações
1,931 avaliações

Sobre o curso

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....

Melhores avaliações

JY

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.

AM

Jul 01, 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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1851 — 1875 de {totalReviews} Avaliações para o Sequence Models

por Ashvin L

Oct 22, 2018

The course content is pretty good for breadth. However, it falls short in going into depth. Assignments need to be more open-ended and probably a bit more involved. It appears that we are cutting and pasting code that is already written in comments.

por Michael K

Aug 06, 2018

Assignments are very buggy and instructions misleading or incomplete. However the core material is excellent

por 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.

por Noam S

Oct 27, 2018

The lectures were not as good as the previous andrew ng. courses, and the exercises were quite bad in all honesty.

I do appreciate what I have learned, as the lectures WERE clear enough.

por Piotr D

Nov 17, 2018

The course does not explain how to use Keras (it's assumed you've finished the previous course). What's more a lot of code parts is implemented in some difficult way (for loops instead of Python's builtins and idioms like any or list comprehensions). I'd love to see more materials on speech recognition.

por Travis J

Nov 25, 2018

The subject matter was a good introduction to various RNN model types and concepts. I have to dock a couple stars, however, as the course leans so heavily on Keras implementations during the assignments that it really should be listed as a firm requirement. While I feel that I'm more experienced with both RNN models and the use of Keras now, it was a struggle with what felt like a lot of cargo culting for me to get through most of the assignments. I don't consider the brief lesson on Keras at the end of the second course to be sufficient training, particularly if much time has passed between taking that course and this one. A brief "Lesson 0" on Keras is sorely needed at the beginning of this course. Otherwise, it should be explicitly and firmly communicated at the start that the programming assignments require a certain familiarity with the Keras framework. Overall, I do highly recommend this course, but be forewarned about the need to be familiar with Keras before starting.

por André T D S

Oct 02, 2018

Bugs in the programming assignments grading kills the flow

por 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

por Aditya B

May 09, 2019

Really interesting course with fascinating applications. However, in terms of difficulty, it is a significant step up from all the previous courses. A lot of time is spent figuring out the syntax even though the concepts are crystal clear. ( Probably as it is a collaboration with NVIDIA). The programming assignments could be improved.

por Yue

Apr 26, 2019

Esperaba que los ejemplos fueran de otra forma

por Bradly M

Apr 17, 2019

The scope of this course was highly relevant to me, but unfortunately many of the class materials were broken or otherwise incorrect, making some ungraded portions of the assignments difficult or impossible to achieve. Activity on the discussion boards indicates many people have tripped over this for at least the better part of a year, but no corrections have been made. This was quite frustrating and wasted a good amount of my time.

por Sravan

Apr 19, 2019

Works as a primer. Assignments aren't that great.

por Gaetan J d B

Jun 17, 2019

fairly more complex and deeper as previous courses. Nice ex. however.

por Gautam D

Jun 17, 2019

To be completely honest, I loved Dr. Andrew's method of teaching. But the assignments just flew over my head because I didn't have enough hours of practice of Keras under my belt. I know Keras is there to make things easy but it's very difficult to just trying to pass the grader. To goal of assignments was fantastic, I mean, generating music, etc. sounds really amazing but I feel that if there was some more time given to make us better in Keras and other technicalities then I would've loved this course much more!

por Farzad E

Jun 19, 2019

I gave 5 stars to other courses in this series but this one doesn't deserve 5 stars. There were many typos and bugs in the assignments compared to the other courses of the specialization.

por karishma d

Jun 20, 2019

very basic ..would have wanted much advance level .

por Ben R

Jun 27, 2019

Courses had some issues with the grader, and there were some instances where the expected output in the assignment didn't match the actual output, despite it being correct.

See forums for a range of complaints on the matter.

por Eero L

Jun 07, 2019

The course content and Andrew Ng are great. The submission process of the assignments is absolutely dreadful. You might get 0 points for correct answers or not, depeding on...well, I have no idea on what. Maybe it's Jupyter Notebook, maybe it's Keras or maybe it's something else. But you must have good search engine skills, since you will most likely spend a lot of time in searching the discussion forum for answers.

por Saumya T

Jun 09, 2019

Codes are not explained. Some codes files are given

por Rudolf S

Jul 15, 2019

Quite a lot of bugs in the first week examples. It took me too much time until I browsed the discussion forums.

por Yevgen S

Jul 22, 2019

I took this course after a long pause after I finished the first 3 courses. I would NOT recommend doing it that way. As a result, I felt rusty on some of the coding practices.

I think the course gives great introductory information on RNNs and LSTMs. The first two weeks of the course are spot on. However, I think the third week is lacking. I had hard time making a connection between the lecture material and the assignments.

por Bill F

Sep 17, 2019

Toward the end of the specialization, there seemed to be a noticeable drop in both the quality of instruction and the programming assignments. Course 5 on sequence models was much more "hand wavy" than Course 4 on convolution models. At the end of Course 5, I'm still not sure if I learned anything meaningful other than filling in a few blank lines of code to complete the assignment. There was much less intuition provided about the nature of recurrent nets, and then translating that to code was foggy. More attention needs to be paid to how and what the framework is actually doing, not just giving hints at filling the blanks.

Finally, the grader especially in week 3 caused me many, many hours of wasted time and frustration chasing phantom problems in the notebook. Coursera and/or deeplearning.ai does not pay much attention if any to solving the grader or other systemic problems.

por Ragav S

Sep 18, 2019

Would like to learn a bit on how back-prop works when using attention.

por 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.

por stdo

Sep 27, 2019

So many errors need to fix.