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Sequence Models, deeplearning.ai

4.8
11,520 ratings
1,320 reviews

About this Course

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....

Top reviews

By JY

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.

By NM

Feb 21, 2018

Hope can elaborate the backpropagation of RNN much more. BP through time is a bit tricky though we do not need to think about it during implementation using most of existing deep learning frameworks.

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1,304 Reviews

By Andrei Voinea

Feb 15, 2019

A very good final for the Deep Learning Specialization. This course has made it very easy for me to understand new research papers that involve LSTM and RNN networks

By Yingyu Fu

Feb 15, 2019

Great course on sequence models! I never hear do detailed course

By Adrian Nedelchev Kazakov

Feb 14, 2019

It was an unbelievable journey through this Deep Learning Specialization! I really felt the power of the tools I obtained during the past 3 weeks that it took me to pass all 5 courses of the specialization. Many of the Programming Assignments are demanding and in the end I could be extremely satisfied that I succeeded in taking them all. Thanks a lot to Andrew Ng and all involved for making this sequence of courses accessible to people like me, and presenting it in such an understandable and interesting way! Now, I can start thinking of the vast potential for using Deep Neural Networks not only in Research and Space Sciences, where my interests are, but also in my daily life. Very many thanks again! AJ

By Lai yi chen

Feb 14, 2019

很棒的課程,我也會推薦我的朋友來學習,時間序列模型真的相當有難度推薦有學習過的朋友來試試看

By Youssef Awny Saadallah Toma

Feb 13, 2019

THANK YOU <3

By 梁礼强

Feb 13, 2019

Andrew is cool!!Nice course!

By Zifei Shan

Feb 13, 2019

Great course teaching state-of-the art NLP technologies. I wish the attention notebook could be improved, and the projects could get more flexible and in-depth. I also wish there could be a Keras tutorial that gives an overview of the framework.

By Oliverio Jesús Santana Jaria

Feb 12, 2019

This course presents an interesting review of several strategies that are part of the state of the art. However, it is impossible to assimilate how they work in the time devoted to each one. The "fill in the blanks" exercises do not help much.

By Wei Lai

Feb 12, 2019

Thank you!! Very much appreciated!

By sreekanth reddy sambavaram

Feb 12, 2019

had some questions and forum is very inactive.. would be good if there is a backup catchign net if one has question on topic