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Отзывы учащихся о курсе модели последовательности от партнера

Оценки: 28,117

О курсе

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....

Лучшие рецензии


30 июня 2019 г.

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.


29 окт. 2018 г.

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.

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26–50 из 3,372 отзывов о курсе модели последовательности

автор: Rohan G

18 июля 2020 г.

Assignments were extremely didactic; there was no room for creativity. They were not transparent and gave a minimal idea of how to implement these things properly. Course moderators did not bother to answer any of my queries, making the course even less intellectually stimulating. The lectures were monotonous, and hence, I was having trouble finding them to be very engaging. Although, the professor did give some insightful points.

In conclusion, I wouldn't recommend this course to someone unless they are extremely novice programmers. Yet, one may refer to the videos to gain some conceptual clarity on specific topics.

автор: Isaraparb L

26 июля 2018 г.

Unfortunately considerably a subpar course compared to the other four in the specialization. Programming assignment is a mess - wrong formulas presented, nowhere near enough Keras's tutorials, etc. Every assignment is passed by browsing the forum looking for help from other people. It is unclear to the point of being annoyed (got someone in the forum cancel his subscription). However, lectures are fine and sequence models cover a wide range of areas/applications, so you can't miss it anyway.

автор: Kiran M

16 февр. 2018 г.

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.

автор: Martin C S

13 июля 2019 г.

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.

автор: Marc B

12 июля 2018 г.

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

автор: Oscarzhao

2 апр. 2018 г.

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

автор: asieh h

13 июня 2018 г.

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.

автор: Jaime G

27 июня 2019 г.

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

автор: AlainH

5 февр. 2018 г.

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

автор: Logos

31 авг. 2020 г.

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.

автор: Moses O

21 июля 2021 г.

The unit tests in the programming assignments are poorly implemented. They will fail you if your code is not exactly as expected, even when it runs and returns the correct output.

автор: Saksham G

19 апр. 2020 г.

TensorFlow and Keras basics are not covered. The course states no pre-requisites as well. This was really disappointing.

автор: Yanzeng L

17 февр. 2019 г.

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

автор: Jason J D

11 сент. 2019 г.

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!

автор: Ozioma N

9 июня 2019 г.

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/ is the best!

автор: Marcin G

1 февр. 2018 г.

Amazing course. Andrew Ng has exceptional talent to explain complicated concepts. I have heard about RNNs in other courses but this is the first course, that actually made me understand them. Highly recommended.

автор: Ahmad B E

4 февр. 2018 г.

Best simple course for Deep Learning. I think this specialization is the best as a MOOC but it can be better as an academic course.

автор: Jizhou Y

1 мар. 2019 г.

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

автор: Oleh S

3 июня 2020 г.

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!

автор: Beibit

25 июня 2019 г.

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

автор: Ravi K S

19 мая 2019 г.

Could have been more thorough like previous courses

автор: Christian M

20 июня 2022 г.

T​he sequence models course was the weakest of the 5 in my opinion. I did not really understand the details of the transformer model.

T​he programming exercises could be better. We had to code a lot of very different stuff without any foundations in tensorflow and keras. My intention to start this course was to get the theoretical background (wich I did) and to learn to apply it using python and tensorflow.

I hoped that I would be able to program my own models after finishing this course but I have to admit I can't. It is not very helpful to follow coding instructions line by line without knowing WHY it should be done this way.

I ama software engineer and don't know how others dive into this with little or no programming experience.

автор: Adrian S

21 мая 2021 г.

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.

автор: Navid A

27 авг. 2020 г.

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.

автор: Zelidrag H

26 июля 2021 г.

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