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

4.8
estrelas
21,557 classificações
2,459 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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1926 — 1950 de {totalReviews} Avaliações para o Sequence Models

por Othman B

Feb 22, 2018

Very interesting courses. I take this as a basis for future applications. I only regret that the exercises are too guided. I can't pretend to be able to accomplish a project in machine learning :-(

I would recommend also to note all the references to the papers, they are helpful.

por Cosmin D

Sep 26, 2018

Great content, assignments are fun and reasonably instructive (although they contain the occasional error and the video editing for the lecture content seems a bit rushed at times). I would recommend this course as an introduction to recurrent neural networks and related ideas.

por Justin G V P

Apr 19, 2020

Very informative and well taught course on sequence models. The amount of content and pacing was just right as not to be overwhelmingly complicated. There are a few bugs here and there in the programming exercise which can lead to a lot of headaches but overall a good course!

por Mikhail M

Jun 12, 2018

Week 3: quite a complected network was used for trigger word detection; however, it is not clear why exactly this architecture was used; specific order of dropout, batchnorm and GRU seems to be a pure magic; at least, a few words why this combination is picked are needed.

por Stephen S

Feb 17, 2018

Course content is excellent, I would have given 5 stars, if the Programming assignments wouldn't have bugs. Fortunately people in forum help out with solving issues with assignments. I believe it's due to the short time frame the course is online and bugs get corrected.

por Viliam R

Mar 24, 2018

While this was the most relevant course for me, I missed how it was focused on "helper functions" instead of core RNN concepts. While I feel like I understand concepts like the Bleu score, I would definitely need to spend more time to fully grasp the RNN architecture.

por Alexander

Jan 24, 2019

Would have been nice to get more extensive training in Keras en Tensorflow because programming excercies were somewhat too pre-compiled at times or other times difficult to code because of scarse knowledge of these packets. Otherwise great lecture material as usual

por Vidar I

Mar 22, 2018

This was a great course and teaches you everything you need to know about RNN to get started doing your own research. With background in economics and finance it would have been nice to have one small assignment with time series data. Beside that, awesome course :)

por Sourish D

May 28, 2018

The grader has some bug.Even with correct output and with no bug in the code, it gives incorrect grading. Firstly the criteria to pass is so stiff(80% means to pass for every function).Secondly the bug in grading function grades incorrect for correct codes.

por Sherif M

May 03, 2019

Andrew Ng does a great job in introducing Sequence models in this course. However, I have the feeling the theory behind all the concepts falls short. There are just too many different subtopics being covered instead of focusing on the main concepts of RNNs.

por Endre S

Sep 18, 2018

This last course of the series while still being excellent, it had a few minor issues in the assignments and was quite hard compared to the previous four. Nevertheless, I still learned a lot from it and I am really grateful for it being available.

por Roberto A

Aug 06, 2018

Very interesting and well taught course. The only disappointment is that it focuses almost completely on NLP. I would have much preferred working on other topics too, like for example time series with LSTM, which instead didn't even get mentioned.

por Jkernec

Feb 15, 2018

You should try to leave access to the previous code I wrote in the previous weeks or help out a little in week2 exercise I really struggled to get some of the code done because I didn't have access to my previous notebooks because you locked them

por Harshad D K

May 04, 2020

This course helps you build the basics for natural language processing using deep learning methods.

The assignments at the end of every week test your understanding of the subject and improves your understanding of the topic. Highly Recommended

por Óscar G V

Jan 27, 2019

It is a very good course. Andrew Ng explanations are very clear and easy to understand with a lot of good examples. On the other hand there are some confusions or errors in the backpropagation part of the programming assignment about LSTM.

por Diego A P B

Mar 07, 2018

While a great introduction on RNNs, I felt there could be another week of lectures given the complexity of the algorithms being explained. Likewise, the programming exercises felt unpolished in some parts, like in the expected outputs.

por Luiz C

Feb 11, 2018

Very good. To make it perfect, would have liked it for the Assignments to have less bugs (cf. LSTM backprop), and a longer course with extra weeks to present LSTM in the context of prediction (finance, weather, pattern recognition,...)

por Michael M

Nov 02, 2018

Great course! only negative is that problems would really hold your hand. I don't think there is any way I would pass a whiteboard test on any of this (then again a course to get me to that level would have to be double this length).

por Jaiganesh P

Feb 18, 2019

The course is really good if you want to get a good understanding on the basics of deep learning. It would have been great if the course had more hand's on assignments than fill in the blanks kind of assignments in ipython notebook.

por Rohit K

Jul 07, 2019

I learnt a lot from this course and the whole specialization. I am grateful to the mentors and instructors. If coursera gives me opportunity I can also be mentor for the specialization to help the newcomers through the assignments.

por Ghassen B

Oct 17, 2019

During the first week, I think that a deeper explanation of the matrices' dimensions throughout the NNs should be given. Indeed, this would be helpful to understand some concepts.

Apart from that, it was an awesoome course, thanks!

por Stéphane M

Jun 22, 2018

The course was good except first week. I did not learn as much as I would like from the programming exercises of week 1. It could be nice to have 4 weeks instead of 3 for this course. Taking more time to cover the week 1 material.

por Abid

May 01, 2018

some topics not explained in detail. Not enough examples to understand some models completely. As an example, I didn't fully understand what are the parameters for the models, their shapes, and how they are used in the model

por Harry L

Jul 16, 2018

Overall it was pretty informational on introducing NLP to me. However, Keras was a little bit frustrating to learn at the beginning. I found out the forum was a very good resource to learn Keras syntax whenever I was stuck.

por Eric C

Jan 13, 2020

Great course! I do feel like I'm just scratching the surface of the types of applications that I can make. I think the coding segments still hold our hands a little too much, but you can't beat the clarity of the lectures.