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學生對 deeplearning.ai 提供的 Sequence Models 的評價和反饋

4.8
19,395 個評分
2,111 條評論

課程概述

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....

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AM

Jul 01, 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.

WK

Mar 14, 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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101 - Sequence Models 的 125 個評論(共 2,085 個)

創建者 Raimond L

Jan 11, 2020

Good course to help you understand how sequence models work and how to apply them for various problems. Majority of topics are explained quite well. Practical problems sometimes could be a challenge, but every problem has hints and a bit of theory provided. Overall this course was a very positive experience and I do recommend it. Special thanks for the people who made this course possible.

創建者 Dmitry T

May 03, 2018

I liked that this course was a bit harder than others in the specialization (well partly because It felt like notebooks were made in a bit of hurry here) but it was a good thing for me, since I had to think more on the programming excercises, read Keras documentation, derive backprop equations - and I believe such engagement with the topic really allows to understand and remember it better.

創建者 Mary A B

Mar 19, 2018

It's been so rewarding to apply what I've learned in the previous courses of the Deep Learning specialization to time-based problems. I feel I have a better understanding of how some of the "magic" technology like virtual assistants and speech recognition work. While the material in the first four parts was also very useful, the specialization would have felt incomplete without this course.

創建者 Leandro O B

Jun 04, 2019

Another outstanding course about Deep Learning.

It teaches Recurrent Neural Networks from the basics up to industry applications such as Speech Recognition and Natural Language Processing. The programming assignments are extremely useful to build strong understanding of the algorithms, which we code "from scratch" with NumPy before using higher level frameworks such as TensorFlow and Keras.

創建者 Simon R

May 13, 2018

Loved the course, Andrew is a great teacher; very impressive ability to explain and give intuition. I can really see how I can build upon this course to help me in what I am doing at work. I think there is definitely some room to go deeper on some of the topics e.g. don't just teach sequence to sequence but also broader uses of recurrent networks. Maybe a follow-up course? ... please???

創建者 Fabrice L

Jul 18, 2018

This module of the specialization is a bit more complicated than the others; at least to me, I found the concepts more difficult to grab.

Anyway, thank to Andrew and his team for this amazing specialization. The lectures are great, the assignments are fun and have interesting examples. A huge amount of knowledge along all the courses. You can tell there is a lot of work behind it.

THANKS

創建者 Apoorv V

Jan 03, 2020

I was about to give this course a 3-star rating unlike the other courses in the specialization, which I have rated 5 stars. The reason for that was the programming exercises in week 1. They are not interesting and do not impart a lot of learning. Please consider improving those. The reason I still gave 5 stars is because of the amazing programming exercises in weeks 2 & 3. Thank you.

創建者 JC Q

Feb 10, 2018

In the continuity of the 4 previous modules, the Sequence Models course is of very high quality, the material is concise but cover a wide range of applications and methods, and is delivered with consistent clarity. The programming assignment gives very good hands challenges. I highly recommend this course to anyone interested in natural language processing or speech recognition.

創建者 Mashrur M

Jun 30, 2019

This is the last course of the Deep Learning journey, and I felt like a learned a lot in it. Sequence Modelling is a different beast compared to non-time series models, but I've mastered it thanks to this course nevertheless. I would recommend this particular course to anyone who has a moderate understanding of deep learning and wants to get into time series analysis and nlp.

創建者 Peter V

Sep 12, 2018

A succinct overview of a number of ideas in sequence models. Some of these were covered in an NYU course I took 4 years ago (embeddings, LSTM), others I had heard about but hadn't had a chance to look into (attention). The assignments were set up to be pretty easy, but I think trying to do them from scratch rather than by filling in code would make for a pretty good project.

創建者 Guy M

Sep 05, 2018

Great introduction to sequence models/RNNs. The real-world examples were very illuminating. Again, as with the previous course in the specialization, I felt some details of how to run/predict NNs using keras were lacking, which could leave a student floundering if they've never used keras before. This is in contrast to some other, much easier, tasks where hints were given.

創建者 Alexander G

Feb 25, 2019

Out of 5 courses offered I think this was the most exciting one as it combines everything learnt so far and teaches how to combine different NN modeling techniques to achieve desired classification/prediction features . For example, it is pretty much clear how one would go about building an app that would describe a picture to blind people and do that in many languages.

創建者 Kévin S

Jul 31, 2018

This short 3 weeks courses will make you work a little, exercice take at least twice the time write. You will learn about the famous LSTM, and how to use it on various tasks.

I'm not sure the 'translation' tasks is a good example but there is lot about it. Not a good example, because it is not state of art, and in the 'translation' business there place only for the best.

創建者 Yogeshwar S

Apr 01, 2018

This is a great course, and a great specialization. The professor explains the concepts across very well, not only in this course but in all courses of the specialization. My only gripe is with the notebook/hub/grading system which especially in this course has acted strange and cost a lot of time. That said I've learnt a lot, and am quite happy with the course content.

創建者 SUJITH V

Nov 13, 2018

Great course overall to learn the basics of sequence models and also get a brief understanding of the state of the art architectures used currently. The programming assignment on trigger word detection gives an insight into the practical machine learning implementation for speech recognition. This course combines both theory and practical advice in a very good fashion.

創建者 Meynardo J

Feb 06, 2018

Excellent course - and specialization! Andrew Ng's special talent is in being able to explain complex and difficult stuff with such clarity that you can actually understand it and follow. I found the exercises in this course tougher than in the previous four, but they were varied, useful, and FUN! Highly recommended to all who what to learn the "deep" in Deep Learning!

創建者 向金芳

Jul 03, 2018

Because my research direction is NLP, so I think this course is very good for me. I learn how to implement the Sequence model such as machine translation 、Attention and so on. But the disadvantage is that there is no whole sequence model process. For me, The bigger problem is data processing and model. overall ,This course is good for me, I learned many from this.

創建者 Matías P B O

Sep 10, 2018

The whole specialization is excellent. I highly recommend doing it. The only minor comment that I add is that Andrew should include some links for further reading (along the courses for each topic or theme). I know that anyone can quickly look up for them in the Internet (and they can be outdated) but that would make the specialization even better in my opinion.

創建者 José D

Nov 06, 2019

This is Course 5 of the Deep Learning Specialization, and the last one. We learn Recurrent Neural Network (RNN) /Sequence Model, which allow translation or trigger word (like "Hey Siri!"). It's a completely different beast than CNN seen in Course 4. Again, nice videos and explanations, and well-designed useful programming assignment (TensorFlow/Keras and numpy)

創建者 Hardik A

Mar 05, 2019

The kind of simplicity with which the course is explained and the amount of knowledge gained is worth the hard work of many months! . . I would like to thank the whole Coursera team and Sir Andrew Ng for creating such a wonderful platform and a big shout-out to all the mentors and community who have replied to the most basic queries in the discussion section.

創建者 Bing H

Jul 28, 2019

Home work assignment notebook has a quick time out issue. It's quite annoying since most of the assignment has lots reading material to fully understand the topic or method. Often the notebook just time out and has to be restarted before move to the next section. Hopefully, it can be fixed or improved.

Overall a very good course to learn about sequence model.

創建者 Jiandong S

Mar 09, 2019

It took me a longer time to finish the course due to busy schedule. But I found it totally worth the struggle to work on the course material. Sequence modeling and processing is an new area to me. The course taught me some basic concepts and gave me a chance to lay hands on through programming exercises. I feel a lot like the topic particularly NLP. Thanks!

創建者 Quentin G

Aug 14, 2018

Très largement plus difficile que tout ce qu'il y a eu auparavant. Un véritable apprentissage et un plaisir surtout sur le Trigger Word Detection qui était très intéressant.

Totally more difficult than anything before. I've acquired true knowledge that I'm very proud of. It was a pleasure, especially for the Trigger Word Detection which was very interesting.

創建者 LOS

Feb 17, 2018

Exercises too basic. Better to do something simpler from scratch, them fill in the blanks on statements like "define a to be a boolean variable initialized to True", and run a bunch of other cells with imported code that hides the actual complexity. These kind of exercises does not add anything to the student. Content of Andrew's lessons is great, however.

創建者 Gaurav K

Mar 23, 2018

Thank you Prof Andrew Ng for sharing the knowledge and experience. It has been truly a great learning during the course specialization. And I always admire the way you structure the course and teach the advanced concepts with such an ease. With the power of AI, we as a community try to solve real-world challenges for better life. Thank you so much!