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Sequence Models,

Оценки: 11,520
Рецензии: 1,320

Об этом курсе

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....

Лучшие рецензии

автор: 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.

автор: 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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Рецензии: 1,307

автор: J. Christopher Bare

Feb 17, 2019

Thanks very much. This course was really fun. I can't wait to try using these ideas outside of class!

автор: Mo Rebaie

Feb 17, 2019

Thank you coursera, Thank you Sir Andrew NG, I just finished the specialization, it seems extremely helpful, It's the most important specialization I have ever seen.

автор: Andrei Kazialetski

Feb 16, 2019

Thank you very much!

автор: 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

автор: Yingyu Fu

Feb 15, 2019

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

автор: 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

автор: Lai yi chen

Feb 14, 2019


автор: Youssef Awny Saadallah Toma

Feb 13, 2019


автор: 梁礼强

Feb 13, 2019

Andrew is cool!!Nice course!

автор: 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.