Chevron Left
返回到 Sequence Models

Sequence Models, deeplearning.ai

4.8
11,520 个评分
1,320 个审阅

课程信息

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....

热门审阅

创建者 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.

创建者 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.

筛选依据:

1,303 个审阅

创建者 Yingyu Fu

Feb 15, 2019

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

创建者 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

创建者 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

创建者 Youssef Awny Saadallah Toma

Feb 13, 2019

THANK YOU <3

创建者 梁礼强

Feb 13, 2019

Andrew is cool!!Nice course!

创建者 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.

创建者 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.

创建者 Wei Lai

Feb 12, 2019

Thank you!! Very much appreciated!

创建者 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

创建者 Jefferson David Rodríguez Chivatá

Feb 11, 2019

Very Good