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Sequence Models,

10,169 个评分
1,192 个审阅


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....


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 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!


1,176 个审阅

创建者 Jonathan Lieberman

Dec 18, 2018

Great lectures on the different structures of Sequence Models for use in Natural Language Processing, Text Translation, and Audio Recognition. There is a lot of material packed into 3 weeks, but this course will help anyone familiar with Deep Learning/CNNs to take a dive into the world of NLP and audio/speech recognition.


Dec 16, 2018

Great one Andrew NG sir!

创建者 Miguel Verdu

Dec 16, 2018

Some of the tests were a bit too easy

创建者 Sidharth Wali

Dec 16, 2018

While I loved listening to Andrew Ng's lectures and I find him very lucid in his presentation and pedagogy, I feel that the practical aspect has suffered -by giving enough hints on how to solve the programming exercises, the challenge is reduced. There were quite a few issues I also faced when connecting to the server which resulted in rewriting the code a couple of times (in hindsight, I should have always made a local copy and tested it before submitting it). I would rather that each of these courses becomes a 2 month course (much like Stanfords convolutional networks course) so that the practical aspect is also given equal weightage. While presenting the lectures, Prof Andrew Ng could also lay it out how you would implement in a particular framework like tensorflow and there should be enough exercises that walk a person through them before attempting the programming exercises.

创建者 A Samuel Pottinger

Dec 15, 2018

Fantastic lectures and helpful quizzes

创建者 Saureen

Dec 15, 2018

Please work on getting the notebooks to work properly. Also very bummed that after canceling my subscription, I won't have access to my homeworks. You guys should give us lifelong access - we paid!


Dec 15, 2018

Wonderful course with beautiful intuitions all around , one thing though bit of more mathematics involved

创建者 Michał Kowalski

Dec 15, 2018

Very good course to start dealing with RNN's.

Thank You Andrew for Your whole specialization. Now i feel like a superhero on a rise

创建者 Sushanta Panda

Dec 15, 2018

Andrew Ng at it best.

创建者 Mukund Chavali

Dec 14, 2018

Best in the series