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Comentários e feedback de alunos de Sequence Models da instituição

26,174 classificações
3,088 avaliações

Sobre o curso

In the fifth course of the Deep Learning Specialization, you will become familiar with NLP models and their exciting applications such as speech recognition, music synthesis, chatbots, machine translation, natural language understanding, and more that have become possible with the evolution of sequence algorithms thanks to deep learning. By the end, you will be able to build and train Recurrent Neural Networks and commonly-used variants such as GRUs and LSTMs; apply RNNs to Character-level Language Modeling; gain experience with natural language processing and Word Embeddings; and use HuggingFace tokenizers and transformer models to solve different NLP tasks such as NER and Question Answering. DeepLearning.AI is proud to partner with NVIDIA Deep Learning Institute (DLI) to provide a programming assignment on Machine Translation with Deep Learning. Get an opportunity to build a deep learning project with leading-edge techniques using industry-relevant use cases. The Deep Learning Specialization is our foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI....

Melhores avaliações

30 de Jun de 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.

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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2876 — 2900 de 3,059 Avaliações para o Sequence Models

por Richard S Z

17 de Mai de 2018

The lectures were OK ... better LSTM tutorial by Chris Olah

The exercises really need some review ... very frustrating ... and not all that illuminating .

The course was a good intro to DNN ... but I think either replace Week 3 - Structuring ML Projects with a course on Keras ... or add a course just on Keras.

por Piotr D

17 de Nov de 2018

The course does not explain how to use Keras (it's assumed you've finished the previous course). What's more a lot of code parts is implemented in some difficult way (for loops instead of Python's builtins and idioms like any or list comprehensions). I'd love to see more materials on speech recognition.

por Suresh D

25 de Mar de 2018

I guess as the subject matter becomes more complex, more training is required on the underlying frameworks being used- Keras, TensorFlow etc. Did not feel that sufficient time was spent on understanding the underlying frameworks. Also the TA work is of spotty quality. But I love the way Andrew teaches.

por Salih T A

5 de Abr de 2020

The assignments were not good i think. Because they explained the consepts too long and complicated as like we've never seen these on lectures. I was waiting assignment to require more insight about architecture and less python programming knowledge. This comment is for week1 assignments in special.

por Christopher C

9 de Set de 2020

Programming assignments were not to the level of the prior courses in the series. Should have more illustration of using Keras/Tensorflow. Assignments either were too spoon fed or there was too little reference information whereas prior courses had a good balance. Many of the keras links are dead.

por Devin F

11 de Mar de 2018

For me, there was a large gap on time between when course 4 and 5 were offered (months). This unfortunately was enough for me to forget everything I learned about Keras.

Of course, this course assumes you know Keras so I was behind for the labs

Material is interesting though.

por Marshall

13 de Mar de 2020

Of the courses in the specialization, this one seemed the least organized and rushed. Some of the assignments had some annoying auto-grader quirks that made troubleshooting a pain. Overall it is still worthwhile, just be ready to search forums for help during the assignments.

por Kerry D

14 de Mai de 2018

Too many thing introduced in programming assignments without explanation. Why the high dropout values? Why sometimes one dropout layer, sometimes two? Many things are just given as a formula, and not explained in a way that would let me make my own network for my own problem.

por Alessandro P

22 de Jun de 2020

The lessons are very good as always, but I'd like to be tested more in the programming exercises rather than literally being told what to do and then fill in missing parts of already completed code. Still super glad I took the specialisation, it has been extremely helpful.

por Mason C

12 de Set de 2018

Had to rate this lower due to problem with the final assignment. Submission and saving situation was a nightmare, I had to redo my work several times. Please fix this, it's a real downer at the end of the course. Otherwise, content stellar as always.

por Ashvin L

22 de Out de 2018

The course content is pretty good for breadth. However, it falls short in going into depth. Assignments need to be more open-ended and probably a bit more involved. It appears that we are cutting and pasting code that is already written in comments.

por Oliverio J S J

12 de Fev de 2019

This course presents an interesting review of several strategies that are part of the state of the art. However, it is impossible to assimilate how they work in the time devoted to each one. The "fill in the blanks" exercises do not help much.

por Jorge B S

23 de Set de 2019

This course gives a nice overview of sequence models. If it is true that I do not have an engineering background, I felt it got sometimes a little bit too abstract as compared to other courses of the specialisation. However, I recommend it.

por arnno b

29 de Fev de 2020

I would advise giving more tutorials about TensorFlow and Keras. Those are your main tools and eventually, in many cases we were only required to complete the gaps which don't give you a true understanding of how to use those frameworks.

por Heming C

8 de Fev de 2018

The programming exercises can be better polished, there was quite a few errors that caused unnecessary confusion to the students. Many times, I felt like I was fighting with the Keras/Tensorflow API rather than solving a ML problem.

por Ben R

27 de Jun de 2019

Courses had some issues with the grader, and there were some instances where the expected output in the assignment didn't match the actual output, despite it being correct.

See forums for a range of complaints on the matter.

por Smith R S

3 de Fev de 2019

Need more detailed explanation and programming assignments are way too easy.I would suggest to make advanced courses for people to improve their knowledge keeping all this courses also considering not all feel it very easy.

por Nikhil Y

1 de Dez de 2020

Video content is excellent but I am not very much happy with the assignment task. There should must also be some video content based on the assignment because the some codes some libraries are not taught.

por Dominik B

27 de Abr de 2020

In comparison with other courses in this specialisation a lot of assignments were poor quality - vague descriptions and code logic (especially week1, asign 2 & 3) or just broken (last week3 assignment)

por Pier L L

14 de Fev de 2018

With respect to the others, this one seems to be prepared almost in a hurry and the learning curve is very steep and sometimes the programming assignment don't have a nice progression as the others.

por saipuneet357 .

2 de Fev de 2020

Videos were really informative and were equally interesting, but I believe that the programming assignments lacked a bit in clarity. The instructions were really unclear, it could have been better

por Lyn S

3 de Abr de 2019

Quite a few bugs or abstractions in this course, in comparison to the others the projects feel a bit rushed and pushed together. Andrews's explanations and video lectures were still great though.

por 田奇

3 de Mar de 2018

this course is the most difficult in deep learning specification, but i think Andrew NG should design more homework for word embeddings and bidirectional rnn, i do not understand how it works yet

por Egnatious P

29 de Abr de 2020

The course was great. However, coming from finance I was also hoping to see some examples which use time series so I can get a picture of how I can extend this knowledge to my specific domain.

por Ioannis B

27 de Mai de 2020

The module was really good in explaining the concepts, but there wasn't any deep dive on the equations and mathematics behind with the results of making the code assignment harder to achieve.