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

4.8
estrelas
21,323 classificações
2,427 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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2001 — 2025 de {totalReviews} Avaliações para o Sequence Models

por Markus B

Dec 05, 2018

Great course. The only tiny flaw is that the introduction to Tensorflow and Keras was a bit shallow so that I struggled a bit with programming these parts.

por Andreea A

Mar 31, 2019

Instructive course with useful concepts. However, there were many more mistakes in the notebooks compared to the previous 4 courses in the specialization.

por Zhou S

Mar 22, 2018

Awesome introduction, but feels like Andrew is a little bit rushing since it is the last course in the series, I dont feel it is as clear as other courses

por SHAHAPURKAR S M

May 16, 2020

Faced issues regarding assignment submissions. Otherwise, the course is perfect. Would upgrade my review to 5 stars if this issue seems to be fixed later

por yesid a c m

Feb 15, 2020

Es buen, algo extenso, pero suficiente para avanzar. Algo importante es actualizar los cursos con los nuevos algoritmos, al menos uno, por ejemplo BERT.

por Ng M M

Aug 19, 2019

This course is quite challenging, but at least the concepts were well explained. Wished that Andrew and his team could conduct a crash course on Keras :)

por Maxim V

Oct 05, 2019

A great intro to RNN, LSTM, GRU, Activation. Programming assignments are rather messy though (unlike those in the other courses of this specialisation).

por Harshit S

May 25, 2019

Great course, I like the practical application and assignments discussed in this course , wish latest research papers were also discussed in the course,

por Jun W

May 16, 2019

This course introduces mainly about RNN, GRU and LSTM. Great assignments. 1 score off for the in-correction in assignments. 4.5 scores from me actually.

por Octav I

Dec 23, 2018

Great lectures, really well explained, assignments could request more from the trainee to devise the logic instead of having it already defined for him.

por Tiago C G M

Mar 03, 2019

The course is really good, I would recommend it to anyone who wants to learn the subject, but it lacks support from the staff in the discussion forums.

por Nicola P

Feb 14, 2018

The lectures are excellent. The assignments are an extremely valid trace of significant deep learning application, while they lack a bit of challenge.

por Alon M

Oct 13, 2018

As always, this course is great. however, for some reason this course is much more difficult then the others, and i feel as if it is packed too much.

por Michael S

Jul 12, 2018

Really good course, like the others. A bit too black box in some of the programming exercises, so I expect to struggle when developing my own models.

por Yifan E X

Apr 10, 2018

The videos are really informative and well structured. However, the exams felt like Keras tests. A detailed Keras tutorial would have been helpful.

por Takeo S

Mar 28, 2019

It was great course,

I wish we have more speech recognition contents

Hope, you add new course a bit focus on audio/speech recognition etc

Thank you!

por Ara B

Dec 31, 2019

too much content and not much chance to exercise. I will suggest for more frequently and smaller programming assignments through out the course!

por Nishant B

Aug 11, 2019

The course is nicely designed and every topic is explained in a very lucid manner by Andrew Ng. Must be done as a beginner in sequence models.

por Suraj S J

May 20, 2019

Simplified content delivered in just the right way to give a perfect intuition of the complex concepts. Really enjoyed doing the whole course.

por Harry D

Jan 17, 2019

Great content, but Andrew often starts his phrases then restarts saying them. Audio could use some cleanup, then this course would be perfect!

por Yunhua J

Jun 12, 2018

Most optional assignments contain bugs/errors. Other than that, this is a great course, just as the 4 other courses in this specialist series.

por 王煦中

Feb 03, 2018

I give 4 star because some fomulas are not correct! Though this course is really great. I can not understand why you made mistakes on fomulas.

por Rohit T

Nov 23, 2018

This one seemed to go through to quickly over the details especially with the word vectors and the LSTM, would have appreciated more examples

por Joris D

Feb 16, 2018

Very good course, though the assignments towards the end were a little too centered around Keras, which I personally don't care for very much

por Leung P L

Feb 22, 2018

The instruction of using Keras in the programming assignment is unclear. There are many bugs as well, hence we have versions 1, 2 and 3 etc.