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

4.8
estrelas
21,641 classificações
2,468 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

WK

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!

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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1876 — 1900 de {totalReviews} Avaliações para o Sequence Models

por Eli C

Apr 29, 2018

Andrew has a very good video-lecture style.

The programming exercises can be a bit frustrating at times for the wrong reasons, but at this point the course has been available long enough that you should be able to find a thread in the Discussion forum that provides enough hints to resolve any issue you might encounter. Nonetheless I appreciate the effort that went into designing the programming assignments.

por Damian S

Feb 20, 2018

Presentation is amazing... Professor Ng always does fantastic job of communicating the material in a clear and easily understood way.

I took the course on the first run-through, and there were still some kinks in the grading process that were a little frustrating to deal with, but hopefully these will be ironed out for later versions.

Thank you, Professor Ng, and everyone else involved. You never disappoint!!

por Michael D

Apr 02, 2018

This course has excellent content. Unfortunately there seems to be a slight drop in quality compared to the other courses in this series, with respect to the programming assignments. I didn't find them to be very clearly explained or illuminating.

I'd recommend the jupyter notebooks be reworked with better explanations and more attention to the notational conventions.

Still an excellent introduction though.

por Jeff B

Mar 02, 2018

The lectures were outstanding (as usual), but the programming assignments (except for the final Trigger Word assignment) were terrible. I spent almost all my time trying to figure out Keras syntax, without ever having a Keras tutorial or anything. If you are going to rely on Keras, you should probably add a tutorial or some references. A lot of wasted time. But other than that, this course was amazing.

por Ishwarya M

Jun 30, 2018

Very good course. I liked the speech recognition part more. I found the assignments involving Keras code difficult to do in both RNN and CNN courses. Without the help of discussion forum i wouldn't have completed the Keras assignments. Thank you all the fellow students and mentors for your contributions to the discussion forum. Thank you so much Andrew and team for putting this awesome specialization :)

por Ivana S

Apr 19, 2018

As the other courses in this series, this is definitely another great course, and explains to details the various sequence models. I gave it 4 stars because I believe it might need some improvements. Compared to the previous courses it felt a little rushed, and had too much new information and long programming exercises for a single week. Maybe it would have been better if it was 4 weeks instead of 3.

por Cristina B

Mar 04, 2018

Always a great course but I would expect to have more lessons on how to use Keras and Tensor Flow API in a better way for who needs to use them in real NLP applications. I still have some doubts on how to use them correctly (for example the use of time distributed layer in the last exercise 'trigger word detection' that we didn't use in the architecture for the exercise about attention mechanism)

por David C

Aug 23, 2018

I really enjoyed this course and learned a lot. The descriptions of GRUs and LSTMs were a little scant, however, and I found myself rewatching the videos trying to get my head around them. The course could be improved by going into a little more detail about the different gates and what it means to train them, or what sorts of information or patterns might be relevant for the training of a gate.

por Lida G

May 26, 2020

I really enjoyed learning this course and gained a lot of knowledge from it. The only challenge that I found was some of the steps of the assignments were not clear. I could resolve them by checking the forum. I would also like to know more about document summary and document similarity, but there was not much content for it. Overall, thanks a lot for putting this valuable content together.

por Anatoly R

Feb 18, 2018

Great material and amazing Andrew Ng (5 stars) but very pure editoral review (videos with a lot of repeats of canceled phrases, pauses, quiz understanding, grader problems, very poorness of mentors support because they can do nothing to help, neither contact deeplearning.ai, in summary it's looks like alpha version of course not release and diserve 3 or even 2 stars), so in total 4 stars.

por Vikram R

Apr 21, 2018

This course is almost as good as the prior four, but some of the lectures lack detail, there are mistakes in some quizzes, and the programming assignments at times are crammed too full of information. You can end up passing through this class without really understanding what's going on, whereas the CNN class does a much better job of forcing you to understand things before you pass.

por Daniel Z

Aug 15, 2018

Excellent lecture content.

Some of the programming assignments are quite poor. Sometimes there are minor mistakes in function descriptions, and other times the whole assignment architecture/plan is not well thought out. If the staff doesn't have resources to improve this, then allow the community to create branches and submit merge requests :)

Overall, I'm happy with this course.

por Paulo V

Jul 11, 2018

The lectures were great, making an advanced subject accessible. The course materials were mostly good -- the exception being the optional (non-graded) assignment in Week 1, which was not well-structured, and failed to reinforce the concepts it was intended to. There were challenges with connectivity to the Jupyter notebook server, which caused much frustration and wasted time.

por Frank H

Feb 19, 2018

In the lecture videos there have been quite a few repetitions and in the programming exercises the necessary Keras background has not been delivered. For this I have to subtract one star.

The course's contents are very inspiring, challenging and interesting at the same time. I'm really looking forward to applying the techniques learned so far to problems in my business life.

por Nicolás A

Feb 19, 2018

The course could have covered topics like time-series modeling for prediction (sales, demand, a machine failure in a factory, etc) that is much more applicable than some of the assignments proposed here (half of them seemed to be just for fun). Also, I am a little dissapointed that the course didn't cover chatbots, which is one of the most widely used applications for RNNs.

por Dawar H

Mar 17, 2020

The course was nice but more mathematics could be taught in the lectures, especially backpropagation in recurrent network. Also I feel there could be one more week in this course where recent models like Transformers and BERT can be taught. Overall a nice course to get familiar with Word Embeddings, LSTM, GRU, and some other topics like Translation and Speech Recognition.

por Edward C

Feb 22, 2018

The discussion felt really complicated at points. Also I was disappointed not to be able to complete the optional assignment for LSTM back propagation. Since it is ungraded, it would have been nice to at least see the correct implementation to learn from. Also there were several errors in the expected values or instructions in the assignments, that were really confusing.

por Shringar K

Jul 28, 2019

The instructor Andrew Sir is excellent in conveying topics, but I just found the last part a bit dry compared to the previous 4.

And the course was a bit too long, even though it said 3 weeks.

But the hands on programming practices in this course, especially is second to none. Top Notch.

One would need to revisit and do it all over again to make it stay inside your head.

por Karl M

Mar 15, 2018

Ths course really shows cutting edge technology such as using deep networks consisting of LSTMs, GRUs etc.. I especially liked the audio trigger word recognition.

The translation with attention exercise is really much harder to understand than any other exercise from that specialization. I admit I have managed to implement it more using intuition than real understanding.

por P M K

Feb 23, 2018

It has been quite a good course to explain the tedious concepts of RNN.

The only reason for a 4 star is there is definitely quite some room to improve upon the content and quality to bring it up to the mark of the previous 4 courses. There are quite a few bugs in the assignments which need to be rectified for the benefit of everyone, hope that it shall be done soon!

por Matt C

Apr 23, 2020

Concur with other reviewers: this class was good, covering a lot of interesting material and with well-structured quizzes & assignments. But the lectures seemed to skip past the sorts of in-depth explanations I wanted, instead just getting to the end point of "this is what this looks like". So good, but not quite as good as previous courses in the specialization.

por Shikhar C

Feb 04, 2019

This course is great to get intuitive understanding of Word Embeddings, RNNs, LSTMs, GRUs and Attention Models.

You will have great explainer videos and some excellent programming exercises. The course does not make you an expert, but it does make you familiar with the above mentioned architectures, so you can independently code and try them on your own solutions.

por Duncan K M

Mar 31, 2018

Really cool applications to work on, but the videos got a little too much into specific applications that may not be relevant most of the time. It was all interesting, but it made this course a lot longer each week. I could have done without a lot of the specifics of certain applications, just because it will be hard to apply/remember the concepts anyways.

por Eric F

Sep 23, 2018

All courses in this specialization are awesome. However, this last course feels a little rushed in comparison with the other 4 courses. While the first 3 courses raise your knowledge of ANN in preparation to the 4th one, it is a little more difficult to understand this 5th course. Likewise, completing the assignments is possible, but more frustrating.

por Robert P

Apr 17, 2018

The content is generally great and well worth it. I wish they would fix some of the errors, especially in ungraded exercises. You end up wasting a lot of time because of them. Perhaps the most frustrating aspect is navigating to the Jupyter notebooks. I wish the links to the notebooks were on the same pages as the Submission and Discussion links.