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学生对 deeplearning.ai 提供的 Sequence Models 的评价和反馈

4.8
25,831 个评分
3,042 条评论

课程概述

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....

热门审阅

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.

筛选依据:

2826 - Sequence Models 的 2850 个评论(共 3,014 个)

创建者 Aditya B

May 9, 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.

创建者 Miguel O

May 24, 2020

It´s a fairly good course, with lots of cool topics covered on it. My main complain would be that the subjects covered are dense enough to be arranged on a four or even five week course. Instead, for some reason, all the stuff has been squeezed within three weeks, which makes the lectures shallow and rather cryptic most of the time.

创建者 Romain L

Mar 25, 2019

The course was great, as ever. But some of the programming exercises were very frustrating. Oscillating from very easy to very difficult, with some unclear (and sometimes erroneous) instructions. I felt this was in sharp contrast with the previous 4 courses of this specialisation, for which the course and exercises were perfect.

创建者 radheem

May 1, 2020

the course covered a lot of essentials and gave me a rough idea of how stuff NLP and sequence models work. Though at the same time the content often left me confused and overwhelmed. the Convolutional Networks course was far better.

Overall its great work and I am thankful for hard work put behind the complete specialization.

创建者 Hans E

Mar 3, 2018

Great lectures, great teacher!

I would have given 5 stars but for the problems in the exercises / grader. Some problems that are know for weeks or even months are not resolved. This causes many wasted hours for many hundreds of students. Please solve this and make it a 5 star course.

Many thanks to Andrew Ng and the mentors!

创建者 Glukhov E

Feb 16, 2020

The programming tasks were very simple. I doubt that you can really learn anything when you just need to copy the text from the task description and paste it. The content of the tasks was excellent, but the level of personal involvement was minimal.

In addition, the information in the course is already outdated.

创建者 Richard S Z

May 17, 2018

The lectures were OK ... better LSTM tutorial by Chris Olah

The exercises really need some review ... very frustrating ... and not all that illuminating .

The course was a good intro to DNN ... but I think either replace Week 3 - Structuring ML Projects with a course on Keras ... or add a course just on Keras.

创建者 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.

创建者 Suresh D

Mar 25, 2018

I guess as the subject matter becomes more complex, more training is required on the underlying frameworks being used- Keras, TensorFlow etc. Did not feel that sufficient time was spent on understanding the underlying frameworks. Also the TA work is of spotty quality. But I love the way Andrew teaches.

创建者 Salih T A

Apr 5, 2020

The assignments were not good i think. Because they explained the consepts too long and complicated as like we've never seen these on lectures. I was waiting assignment to require more insight about architecture and less python programming knowledge. This comment is for week1 assignments in special.

创建者 Christopher C

Sep 9, 2020

Programming assignments were not to the level of the prior courses in the series. Should have more illustration of using Keras/Tensorflow. Assignments either were too spoon fed or there was too little reference information whereas prior courses had a good balance. Many of the keras links are dead.

创建者 Devin F

Mar 11, 2018

For me, there was a large gap on time between when course 4 and 5 were offered (months). This unfortunately was enough for me to forget everything I learned about Keras.

Of course, this course assumes you know Keras so I was behind for the labs

Material is interesting though.

创建者 Marshall

Mar 13, 2020

Of the courses in the specialization, this one seemed the least organized and rushed. Some of the assignments had some annoying auto-grader quirks that made troubleshooting a pain. Overall it is still worthwhile, just be ready to search forums for help during the assignments.

创建者 Kerry D

May 14, 2018

Too many thing introduced in programming assignments without explanation. Why the high dropout values? Why sometimes one dropout layer, sometimes two? Many things are just given as a formula, and not explained in a way that would let me make my own network for my own problem.

创建者 Alessandro P

Jun 22, 2020

The lessons are very good as always, but I'd like to be tested more in the programming exercises rather than literally being told what to do and then fill in missing parts of already completed code. Still super glad I took the specialisation, it has been extremely helpful.

创建者 Mason C

Sep 12, 2018

Had to rate this lower due to problem with the final assignment. Submission and saving situation was a nightmare, I had to redo my work several times. Please fix this, it's a real downer at the end of the course. Otherwise, content stellar as always.

创建者 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.

创建者 Oliverio J S J

Feb 12, 2019

This course presents an interesting review of several strategies that are part of the state of the art. However, it is impossible to assimilate how they work in the time devoted to each one. The "fill in the blanks" exercises do not help much.

创建者 Jorge B S

Sep 23, 2019

This course gives a nice overview of sequence models. If it is true that I do not have an engineering background, I felt it got sometimes a little bit too abstract as compared to other courses of the specialisation. However, I recommend it.

创建者 arnno b

Feb 29, 2020

I would advise giving more tutorials about TensorFlow and Keras. Those are your main tools and eventually, in many cases we were only required to complete the gaps which don't give you a true understanding of how to use those frameworks.

创建者 Heming C

Feb 8, 2018

The programming exercises can be better polished, there was quite a few errors that caused unnecessary confusion to the students. Many times, I felt like I was fighting with the Keras/Tensorflow API rather than solving a ML problem.

创建者 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.

创建者 Smith R S

Feb 3, 2019

Need more detailed explanation and programming assignments are way too easy.I would suggest to make advanced courses for people to improve their knowledge keeping all this courses also considering not all feel it very easy.

创建者 Nikhil Y

Dec 1, 2020

Video content is excellent but I am not very much happy with the assignment task. There should must also be some video content based on the assignment because the some codes some libraries are not taught.

创建者 Dominik B

Apr 27, 2020

In comparison with other courses in this specialisation a lot of assignments were poor quality - vague descriptions and code logic (especially week1, asign 2 & 3) or just broken (last week3 assignment)