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

4.8
estrelas
27,217 classificações
3,243 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

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.

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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26 — 50 de 3,239 Avaliações para o Sequence Models

por Kiran M

16 de Fev de 2018

This course felt rushed. Especially, the programming assignments, which had many errors and were frustrating at time. It is still worth it since the content is really good -- only if you are willing to go through the frustration during the programming exercises.

por Martin C S

13 de Jul de 2019

Assignments don't match the quality of the other four courses of this specialization. Automatic grading accepts solutions despite results not matching expected results. This should be fixed.

por Marc B

12 de Jul de 2018

This one went a little fast for me, can't say that I'm confident on the shapes of tensors going through RNNs and why

por Steffen R

4 de Fev de 2018

super unorganized!

really really bad

por Wonjin K

14 de Mar de 2018

I was really happy because I could learn deep learning from Andrew Ng.

The lectures were fantastic and amazing.

I was able to catch really important concepts of sequence models.

Thanks a lot!

por Jaime G

27 de Jun de 2019

Some coding assignments were too hard to follow what was required.

por AlainH

5 de Fev de 2018

This course has many inconsistencies and errors in the homework. Seems like a rushed job.

por Oscarzhao

2 de Abr de 2018

some optional exercises are wrong, wasted a lot of time on LSTM backward propagation

por asieh h

13 de Jun de 2018

It was difficult to follow the programming exercises because many of it had already been written. I think it would be more useful to learn one framework instead of using both keras and tensorflow in one course. I still don't know how to debug any of these frameworks. Without the forums, it would be very difficult to pass the assignments. Sometimes there were bugs in the jupyter notebook, sometimes typos that were misleading. As a result, it took me many hours stuck on one assignment. It would be good if these comments are taken into account for the future classes of this course. I really enjoy Andrew Ng.'s courses but I was disappointed at this last course's assignments.

por Yanzeng L

17 de Fev de 2019

There are a lot of mistakes in programming assignment. Please update and fix it

por Jason J D

11 de Set de 2019

Wonderful end to this Deep Learning Specialization. The programming assignments cover up a variety of hot topics in the Deep Learning market. The videos are very well made and teach the content in depth. A special thanks to Prof. Andrew for yet another amazing course in this wonderful specialization!

por Ozioma N

9 de Jun de 2019

Great module, I am lucky to have used this resources in learning sequence models, I can imagine running LSTM using one of the frameworks without ever implementing it myself, Andrew Ng/Deeplearning.ai is the best!

por Jizhou Y

1 de Mar de 2019

Professor Andrew is really knowledgeable. I learn a lot from his lecture videos.

por Oleh S

3 de Jun de 2020

Very good course which gives a nice intuition to sequence deep learning modelling. Unfortunately, this is the weakest one among the whole specialization. There are no deep explanation of LSTM as well as GRU and back-propagation algorithm. Seq2seq models explanation is not clear and looks too inconsistent. I had to read a lot of the additional materials and blogs in order to understood a theory behind lectures. Hence, the first week assignments were disagreeably difficult to complete, whereas second and third week assignments were comparatively easy. I think this course should be revised or prolonged for 4 weeks to cover LSTM models more profoundly. Nevertheless, I would like to thank Prof. Andrew Ng for really great job and initiatives in such an important area of study!

por Beibit

25 de Jun de 2019

Little bit math heavy. It was sometimes hard to understand the intuition, e.g. RNN, LSTM, GRU

por Ravi K S

19 de Mai de 2019

Could have been more thorough like previous courses

por Adrian S

21 de Mai de 2021

I would really like to give this course 5 * but the finally programming assignment was a disappointment. It seems many other folks feel the same way. I found myself spending many hours trawling the the web for additional background.

por Navid A

27 de Ago de 2020

The first week is amazing. The last week is the worst! Andrew starts nicely; but as he goes to the second and third weeks, he hardly explains why he does what he does.

por Zelidrag H

26 de Jul de 2021

Week 4 coding exercise is incomparably harder than any other in this entire specialization.

por Siddharth S

29 de Mai de 2021

The transformer subclass programming exercise is super useless task. Spent hours on this task and learnt nothing.

por chao z

22 de Fev de 2018

If it could improve assignment accuracy, it will be better

por 宇翔 蔡

6 de Mar de 2018

there are a lot of mistakes in programming assignments.

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 Ahmad R S

3 de Abr de 2020

I will remember this course for all bad reasons. Poorly written programming assignments. These things not only wasted the time but days in doing the nonsense. It must be understood that people who are enrolled in such courses and specializations are doing it in their part-time and wasting their time in solving someone else's crap is totally not acceptable. I will never recommend this specialization to anyone. It is a waste of resources (time, money and energy).

por Zhongyi T

11 de Jun de 2019

Poor submission system. Failed many times to upload and had to redo the assignments. I was using a 250Mbps high speed network. Also course materials are problematic. The instructors are not willing to fix the problems for many years.