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学生对 提供的 Sequence Models 的评价和反馈

25,925 个评分
3,054 条评论


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....


Jun 30, 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 29, 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.


2701 - Sequence Models 的 2725 个评论(共 3,025 个)

创建者 Anugna R

Jul 15, 2020

codes are too long and it is taking time for codes to run

创建者 Hassan E

Mar 2, 2019

Greeeeeeeeeeeeeeeat but less than the first four courses.

创建者 KIT M C

Nov 13, 2019

The program in the exercise is a bit hard to understand.

创建者 Galvin W

Feb 23, 2018

Good when it came. Annoying for the 2 month launch delay

创建者 David N

Apr 26, 2020

i'd like to have applications more suited to real world

创建者 Vikas K

Mar 31, 2019

it would have been better if he used more visualization

创建者 Jarosław G

Jan 21, 2019

There were a lot of problems with notebook task grader.

创建者 Nick J

Mar 11, 2018

Great course, but too many mistakes in the assignments.

创建者 Aloys N

Oct 22, 2019

Good content, it would have been good to do more keras

创建者 Johannes J

Jun 27, 2019

Great insights, helpful notebooks, good explanations.

创建者 Karol K

Feb 26, 2018

Again, programming assignment should work flawlessly!

创建者 Roberto G

Apr 5, 2020

un poco lentos los ejercicios y repetitivos comandos

创建者 Saurabh P

Feb 17, 2018

Very good introduction to RNNs and their variations.

创建者 Jetro G K

Jul 24, 2018

Muy difícil en comparación con los demás anteriores

创建者 阿刘

Aug 6, 2020


创建者 Minh N

Jan 4, 2020

Too much details! Too little time. More exercises!

创建者 Igor R

Apr 20, 2018

Excellent content, the auto-grader not so awesome.

创建者 Andriyanto H

Apr 18, 2018

Very good course but can be too rushing sometimes.

创建者 Syed S

Feb 1, 2020

A little too difficult to understand from scratch

创建者 ANDREW ( G

Jan 20, 2020

A little bit less quality than the previous ones.

创建者 Hemanth M

Jul 31, 2019

More programming examples/exercises would be good

创建者 tusheng w

Apr 18, 2018

useful to familiar with RNN, GRU, LSTM and so on.

创建者 SuperChen

Feb 12, 2018

Exercises are a bit tough and misunderstanding...

创建者 Wan N

Apr 15, 2020

It will be nice if the videos are more detailed.

创建者 Marco M

May 17, 2018

The course was really interesting and well done