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

4.8
18,065 classificações
1,958 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

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.

SD

Sep 28, 2018

Great hands on instruction on how RNNs work and how they are used to solve real problems. It was particularly useful to use Conv1D, Bidirectional and Attention layers into RNNs and see how they work.

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126 — 150 de {totalReviews} Avaliações para o Sequence Models

por Sharath G

Feb 22, 2019

Deep learning specialization is one of the best courses I've ever done. When I used to work on Computervision prior to this course, I used to stumble a lot conceptually and in implementation. This specialization gave me a pragmatic insight into the DL. Can't thank coursera, deeplearning.ai and instructors anymore. :)

por Fabian A R G

Feb 21, 2019

Well organized, concepts are explained clearly. Fun assignments. I felt this one was the toughest, but that made it more interesting.

por Santiago I C

Feb 21, 2019

Perfecto complemento al resto del cursos de la serie.

por Brian ( B

Feb 22, 2019

More lectures are needed in the sequence models to make these models or ideas clear to deep learning learners. I found this course is the most difficult one to follow in this series even if I got quite a lot experience on time series topics.

por Paul D

Feb 23, 2019

As someone who loves NLP, this course was great. Would recommend to others.

por Elad A

Feb 24, 2019

Thanks for this wonderful course specialization! I enjoyed it very much and learned a lot!

por Fernaldy A F

Feb 24, 2019

Great course.. Thank you for providing it

por Sam D

Feb 25, 2019

Awesome course and specialization. Now, to implement everything I learned in my own programs, and of course I will be sure to revisit the videos until everything becomes second nature. Learn, program, improve and repeat. Thanks!

por Wadigzon D

Feb 24, 2019

excellent, I did some speech recognition & neural nets in the past, I am surprised at how much the field has evolved, this was a great refreshener

por HARENDRA S

Feb 25, 2019

Very good course.

por Yan-Jen H

Feb 25, 2019

Nice course :)

por Alexander G

Feb 25, 2019

Out of 5 courses offered I think this was the most exciting one as it combines everything learnt so far and teaches how to combine different NN modeling techniques to achieve desired classification/prediction features . For example, it is pretty much clear how one would go about building an app that would describe a picture to blind people and do that in many languages.

por Hristo B

Feb 25, 2019

Most notably, an exercise guides one through the building of a recurrent network from scratch. More exercises show the value of different architectures and make the learner proficient in using neural network libraries (Keras).

por Zynab S

Mar 21, 2019

Yes, I have just finished the whole specialization. I'm very proud of myself. And I recommend this specialization to anyone who wants to start with this field. Andrew is the best one I've seen who able to explain the thing in deeper way. Thanx

por Mohd H

Mar 21, 2019

Attention mechanism was best

por Paweł T

Mar 21, 2019

Big improvement on this field

por WALEED E

Mar 20, 2019

This course was quite amazing in understanding with top papers discussed how machine translation and word trigger detection is carried using RNN. Code assignment was the best to show detailed steps of building RNN with a lot of hints to keep you moving forward

por Phongvasu S

Feb 27, 2019

Such a great specialization as a whole. Recommend for anyone.

por Utkarsh G

Feb 27, 2019

The course is good but I like the other courses of the specialization a little more.

por Yilei Z

Feb 27, 2019

very intuitive and knowledge rich

por TanBui

Feb 28, 2019

This is the last and very good course. The last assignment was very interesting.

por Himansh C

Mar 24, 2019

Thank You Prof. Ng! Kinda sad that this journey is over but looking forward to applying all that I have learnt. :)

por Ian T

Mar 22, 2019

Amazing

por Martin B

Mar 22, 2019

Very very interesting but it's a lot more difficult than the other courses. I did it out of sequence (no pun intended) (i.e. I skipped Convolutional networks to go straight to RNN, because they interest me more).

That wasn't the correct move. I barely knew anything about Keras, the exercises took a LOT more time. Still, it's a wonderful course.

por Nguyễn V T

Mar 22, 2019

i love it