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16,601 Bewertungen
1,814 Bewertungen

Über den Kurs

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. 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....



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.


Oct 30, 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.

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76 - 100 von 1,793 Bewertungen für Sequence Models

von Michael O

Jan 31, 2019

Very good for understanding how recurrent neural networks work. Highly recommended

von Sarthak P P

Feb 02, 2019


von CUI

Feb 03, 2019

great courses, big thanks to Andrew Ng

von Joachim D

Feb 03, 2019

Great course, very clear presentation and interesting examples on how to prepare data and how to use keras. Very interesting on how easy it is to build & train complex networks with keras (once you have the data..)

von Pavel K

Feb 05, 2019

This course offers a great introduction to the models: RNN, GRU and LSTM.

In addition, it illustrates the power of "Word Embedding" and "Attention Model".

The programming assignments are interesting, provide deeper understanding of the models, and show how simple it is to implement these models in Keras.

von Bruno G C

Feb 05, 2019


von Zhaiyu C

Jan 26, 2019

A bit harder than previous courses. Pretty well organized as always.

von Prateek G

Jan 26, 2019

This was a tough one. The specialization is well structured and slowly progresses in terms of complexity. Having worked on RNN, i thought I would ace the projects. Different story though at the end

von Raed C

Nov 20, 2018

Very didactic course and very good lessons on sequence models applications

von mvpzhao

Nov 20, 2018

very good lesson, thanks Andrew Ng

von Artem B

Nov 20, 2018

This is again a fantastic course and what a nice way to finish the Deep Learning Specialization. It is certainly the most difficult one from the whole specialization and has taken me a lot longer than I planned. This is partially due to the fact that focus is shifted a bit more towards the programming assignments and concepts that are only briefly mentioned in the lectures turn out to be crucial for the assignments. The forum helps a lot, without it I would not have been able to crack the first week, especially the optional parts of the assignments. There were also a few errors in derivation formulas, that had set me back, but in the end I understood the concepts a lot better and found some nice complementary resources online. And the RNNs are more complex and seem more variable than other network architectures, so that is ok that this course is more difficult. Now I feel that I finally have a good grasp of Deep Learning concepts and have a nice set of skills. And the assignments are super fun and very useful. Thank you Andrew Ng and your team for making such a wonderful content. I teach at the university-level and I can only imagine how much effort goes into preparing such a course and at such a high level of expertise. I encourage everyone to take this specialization, this specialization is the main gem in Coursera, in my opinion.

von Max B

Nov 21, 2018


von Toru H

Nov 21, 2018

I really enjoyed this course!

von Pham X V

Nov 06, 2018



von Jun W

Nov 06, 2018

Concepts are covered very well. They are not very easy to grasp. But Professor Ng makes it easy. Hopefully, I will practice some of the knowledge.

von Khaled A M A

Nov 06, 2018

thanks a lot coursera for the financial aid 5 times and save my life and thanks a lot for the whole specialization

von zhiqing h

Nov 24, 2018

Very detailed hands-on assignment. Hard tho

von Srivathsan A

Nov 24, 2018

Awesome conclusion to deep learning. The 1 side trigger detection algorithm is good final touch. Thank you Andrew NG..

von Shariq A

Nov 23, 2018

Thank you Sir for making the course easy and possible for me to learn.Thanks a lot

von Ethan ( H

Nov 23, 2018

Andrew is my idol

von Veeresh S

Nov 24, 2018

Thank you Andrew NG for teaching AI

von Alina P

Nov 23, 2018

Completed Deep Learning specialization in the I really liked this course, it will be useful not only for the beginners, but also for the specialists, which want to have an overview about current neural networks trends and see the interview from the best specialists of AI. To make this course perfect I would recommend to fix some errors in the theory of programming assignments (specially in the last 2 courses). Sometimes this issues are confusing and forcing to check on the forums correctness of the task.

von Flavio R d A

Nov 09, 2018

Great course! The practical exercises are awesome!

von jaylen w

Nov 08, 2018

Finally I finished the whole series of Deep Learning AI, through which I gained a lot of intuition of deep learning algorithms and its implementation. It's great course to get into this new era especially with a excellent teacher like Andrew who really illustrates the core ideas of deep learning algorithms to me.

von Jhon S

Nov 26, 2018