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

4.8
estrelas
25,888 classificações
3,049 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
29 de Out de 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.

WK
13 de Mar de 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!

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351 — 375 de 3,021 Avaliações para o Sequence Models

por Beltus W N

19 de Out de 2020

After finishing this course, I'm so fired up by the potential projects I can build with this knowledge that I feel adrenaline coursing through my veins. Thank you Prof. Andrew Ng. Thank you Deeplearning.ai team. You're the best.

por Shashti K N M

8 de Jun de 2020

The Course was Excellent. Sir's teaching was Excellent. I understood the techniques of Sequence Models and Natural Language Processing. The Programming Assignments were Excellent. The Deep Learning Specialization was Excellent.

por George Z

29 de Set de 2019

Amazing course and what a finish line. I only with the graded assignments are revisited as few of them have bugs in them. Also I hope the Word2Vec algorithm and word embedding in general is explained better and with exact steps.

por Sam D

24 de Fev de 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 Himanshu G

26 de Abr de 2020

This was particularly intensive course of this whole series, learned a lot.

Thanks to Prof. Andrew NG, accept a Natmastak Pranam from this Student of yours, will always be indebted for what I have learned here. You are the Best

por Rahi A

8 de Jan de 2020

I have many of books and blogs related to RNN, but was not clear and confident about it. And after studying only the first week video and lectures, I am so confident and happy that cant tell you!!! Thank you so much Andrew...;)

por leonardo d

4 de Dez de 2019

It seems like there are several and very useful RNN models. Many of them are very good at specific tasks, and if you take this course you will be abe to understand and implement many of them. It was a really amazing experience.

por Sandeep P

27 de Jun de 2018

An excellent introduction to the theory and practice on recurrent deep neural networks. Great usage of all the 4 courses in this series to culminate with this course as a great finish to deep learning theory and implementation.

por Rafael E

10 de Fev de 2018

Yet another amazing class! I'm so grateful for the existence of these classes. It makes mastering deep learning very much easier. My thanks to Andrew, and all others who have worked so hard to make this course possible! :-)

por Hristo B

25 de Fev de 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 Aparna D

30 de Out de 2018

This was quite a tough one.. But it was almost magical when the outputs of the assignment were successfully completed. Excellent. The discussion forums helped a lot, as the instructions were not very clear to novices like me.

por Jeffrey T

2 de Abr de 2020

Amazing course, Andrew Ng presents the material in a concise and intuitive manner. It would be nice to have access to all of the material needed to fool around with the assignments on our computers in an offline environment.

por Dmitry N

6 de Out de 2019

Thank you for this wonderful sequence of courses! This whole concept is still a bit blurry for me, but as a lot of people during the interview have mentioned, one must simply exercise new skills to understand the technology.

por Gopi P V R

16 de Mar de 2019

It's great course to get concepts right and overview. It will be great if you add further programming assignments(other than partially coded ones) or resources as such where one can practice what he had learned as optional.

por Nick S

30 de Mar de 2018

Great choice of material, i would be happy to have one more week of that course to see more examples and have more time to familiarise with the concepts. All weeks were very useful and all the material was greatly explained.

por Yousif M

28 de Dez de 2020

I enjoyed all the courses of the specialization but I was looking forward to Sequence Models the most. I think a lot has been covered in this course and I can't wait to try working on projects with the knowledge I now have.

por Severus

5 de Jun de 2020

This course is good , I learn RNN,LSTM,GRU etc.Just one thing, the last assignment is hard to submit.I guess maybe there is a systematic problem that need to be solved. Everything except that is great. Thanks a lot, Andrew.

por Seungbum H

3 de Jun de 2020

This is an excellent course for a beginner like myself. I would like to thank Andrew for making this course available to everybody in the world. Thank you so much for your inspiring course. With best regards, Seungbum Hong.

por Salman A

23 de Abr de 2020

This course has helped me in developing an understanding for implementing sequence models through Recurrent Neural Networks that can be used in number of applications such as Natural Language Processing and Audio detection.

por 蕭博偉

22 de Jan de 2020

A briefly introduction of Sequence Models to solve sequence problem, such as translation, speech reorganization..etc. Homework is also very helpful to understand what is going on step by step under Recurrent Neural Network.

por Moses W W

3 de Nov de 2018

This is an excellence training course! I had a wonderful experience learning the leading edge Artificial Intelligence knowledge specialized with Deep Learning and believe this will make a life-long impact to my career path!

por Gurprem S

18 de Nov de 2020

Excellent Course! The maths and concepts were a bit tough to understand and I had to look up some(a lot) of stuff but the learning experience and the thrill of actualling building and training the model is very satisfying

!

por BA M

25 de Abr de 2018

My favorite by far, and I'm not a fan on NLP. Sequence Models, especially attention mechanisms seem to have so much potential. Interested in using them to look at time series data analytics for industrial iot applications.

por Sorin G

21 de Abr de 2020

Excellent Course by Professor Andrew NG, I enjoyed learning what lays under the concept of Deep Learning and Neural Networks.

Thank you very much to Andrew Bg and the team, and as well the mentors supporting the students.

por Junfei S

9 de Dez de 2018

The course content is great overall! The only thing I am a little unhappy is that one or two of the programming exercises have confusion instructions. But finally I made it under the help of peers on the discussion forum.