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

4.8
estrelas
26,603 classificações
3,146 avaliações

Sobre o curso

In the fifth course of the Deep Learning Specialization, you will become familiar with sequence models and their exciting applications such as speech recognition, music synthesis, chatbots, machine translation, natural language processing (NLP), and more. By the end, you will be able to build and train Recurrent Neural Networks (RNNs) 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. The Deep Learning Specialization is a 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 take the definitive step in the world of AI by helping you gain the knowledge and skills to level up your career....

Melhores avaliações

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!

AM
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.

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3076 — 3100 de 3,117 Avaliações para o Sequence Models

por SARAVANAN N

19 de Mar de 2018

Overall a great course, thanks to Andrew NG for his great explanations. But a very bad support, I faced many issues in submitting the assignment due to technical issues (notebook not saving) but no dedicated resource to help me. I spend lot of time in resolving my self.

por Sergei S

18 de Mai de 2019

Feels again like authors tried to put everything into just a couple of weeks, thus the course turned out to be messy with lots of details hidden. Even though there was a lot to learn, I am still not sure if I understand correctly how to build a simple sequence model.

por Clement A

7 de Ago de 2020

Really good to understand the basics, however, it doesn't use the latest TF2 and the exercises are either trivial because too much pre-worked, or too hard because it doesn't give the information required to succeed.

This course really needs to be updated.

por Mladen M

9 de Jul de 2020

Programming assignment instructions are not well written (clear), and as a result it is easy to get stuck on something of little relevance to deep learning. Also, I would suggest that you make the lecture notes in written format available.

por Chris M

21 de Ago de 2019

The lectures cover the basic design of the models but don't help teaching you how to actually use them. I learned more by reading blogs to get the programming assignments to work then this course.

por Ashley H

14 de Set de 2018

Lectures/Videos were excellent, the assignments were very poor (loads of errors in the code not corrected over 7 months since the course went live)

por yuvaraj

11 de Dez de 2020

The course videos were very lengthy and difficult to follow. Many topics discussed in course video were not part of programming assignment

por Simeon S

18 de Mar de 2020

Good introduction to the concepts. Really poor quality videos and exercises. Very frustrating when working on the assignments.

por David L

28 de Jun de 2020

Good lectures. Programming assignments are useless fill-in-the-blank exercises, you don't really learn much from them.

por Thomas A

10 de Out de 2019

The programming assignments really are like pulling teeth. There's not really enough guidance leading up to them.

por Mark

24 de Out de 2018

The course videos and the programming assignments were lacking. And there was no support in the forums.

por Jeffrey S

2 de Jun de 2018

Spent more time trying to work around a buggy grader than learning the underlying concepts.

por ZHANPENG T

23 de Out de 2019

Too hard to understand compared to the previous coursed in this specification.

por Hamid A

13 de Nov de 2020

Was very difficult. please add more expiation of mathematical equations.

por Sukeesh

18 de Abr de 2020

Little unsatisfied with the final part of the specialization.

por Arsh K

20 de Ago de 2019

Lack of Keras training made it often hard to do layer code.

por Tom T

9 de Jan de 2020

This course needs more instruction on Keras.

por Mark N

12 de Fev de 2018

Poor explanation for alot of things

por Milica M

10 de Mai de 2020

boring and uninformative

por João P B D

4 de Jan de 2019

Too difficult.

por Martin B

11 de Mar de 2018

Needs work.

por Alex L

5 de Mar de 2018

I feel sad.

por zhesihuang

3 de Mar de 2019

sucks

por Logos

31 de Ago de 2020

I have no idea how we're supposed to walk out of these courses with the knowledge of how to build a neural network. The practice exercises are a joke. It's a bunch of functions taken out of context, with "instructions" on how to complete each. I don't understand how to do any of it, and I passed all the quizzes.

This specialization gets good reviews because people love Andrew, and although I'm sure he's a great guy, these courses provide no real practical information on how to build neural networks from scratch. I don't even know where to begin, and at this point I'm just copying solutions from the internet to complete the projects so I can just get my completion certificate.

I only recommend taking this from a theoretical perspective. If you're looking to get started with deep learning from a practical standpoint, look elsewhere. This isn't worth it.

por Aldiyar K

12 de Mar de 2021

Oversimplifying material, such as not showing any math foundations and proofs, does not lead to an intrinsic understanding of the material as well as fill-the-gap assignments do not enhance comprehension.

I understand that the course is intended for the broad audience but will one be able to implement those Keras and TensorFlow algorithms on a moderately complex problem, which is the ultimate goal of these courses? Highly doubt it because the code is pre-written for students and step-by-step guide is provided. In my opinion, one could go straight to assignments and induct / deduct the answers.