Chevron Left
返回到 Sequence Models

學生對 deeplearning.ai 提供的 Sequence Models 的評價和反饋

4.8
18,120 個評分
1,964 個審閱

課程概述

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....

熱門審閱

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.

AM

Jul 01, 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.

篩選依據:

26 - Sequence Models 的 50 個評論(共 1,941 個)

創建者 Kiran M

Feb 16, 2018

This course felt rushed. Especially, the programming assignments, which had many errors and were frustrating at time. It is still worth it since the content is really good -- only if you are willing to go through the frustration during the programming exercises.

創建者 宇翔 蔡

Mar 06, 2018

there are a lot of mistakes in programming assignments.

創建者 chao z

Feb 22, 2018

If it could improve assignment accuracy, it will be better

創建者 Kirk P

Jul 01, 2018

The lectures were great. Andrew is a wonderful teacher, but the assignments were beyond miserable. Jupyter notebook is probably the least stable, most infuriating piece of software that I've been forced to interact with. I spent countless hours trapped, not able to perform the most basic of operations, such as saving my work or submitting. I lost work innumerable times. I, like others, eventually resorted to "saving" my work by copying it into a text editor on my system for fear of Jupyter sabotaging me. Even if the system was stable, most of the assignments were worthless as learning experiences. The majority of "programming" boiled down to playing a cryptic game of fill in the blank. Bottom line, I wouldn't recommend this class to anyone in its current state. Especially as a paid service. I really expected better quality.

創建者 Oscarzhao

Apr 02, 2018

some optional exercises are wrong, wasted a lot of time on LSTM backward propagation

創建者 Isaraparb L

Jul 26, 2018

Unfortunately considerably a subpar course compared to the other four in the specialization. Programming assignment is a mess - wrong formulas presented, nowhere near enough Keras's tutorials, etc. Every assignment is passed by browsing the forum looking for help from other people. It is unclear to the point of being annoyed (got someone in the forum cancel his subscription). However, lectures are fine and sequence models cover a wide range of areas/applications, so you can't miss it anyway.

創建者 Juan F C U

Jul 12, 2019

Many topics are only quickly skimmed over. Serves as an overly brief introduction to RNN.

創建者 Martin C S

Jul 13, 2019

Assignments don't match the quality of the other four courses of this specialization. Automatic grading accepts solutions despite results not matching expected results. This should be fixed.

創建者 Yanzeng L

Feb 17, 2019

There are a lot of mistakes in programming assignment. Please update and fix it

創建者 Tom

Sep 04, 2018

Videos are okay, but exercise is just debuging!

創建者 Steffen R

Feb 04, 2018

super unorganized!

really really bad

創建者 Zhongyi T

Jun 11, 2019

Poor submission system. Failed many times to upload and had to redo the assignments. I was using a 250Mbps high speed network. Also course materials are problematic. The instructors are not willing to fix the problems for many years.

創建者 Banipreet R

Jun 28, 2018

Professor Ng seems a little bit confused about the subject and is making unnecessary analogies rather than going deep into the algorithm and explaining the context as he did in Convolution Neural Networks course. I hope that the videos are revised and professor explains the topic more clearly rather than depicting himself to be confused as well on the topic.

創建者 Bhaskar D

Dec 12, 2018

Excellent course. Highly recommended!

創建者 Yoan S

Dec 11, 2018

Excellent state of the art deep learning models made easy. Great job Andrew! And THANKS SO MUCH!!!

創建者 Daniel G

Dec 11, 2018

Auch der Letzte Kurs war sehr gut! Diese Spezialisierung hat sich sehr gelohnt. Der Stoff wurde gut erklärt und war sehr gut anwendbar.

創建者 Jhon S

Nov 26, 2018

cool

創建者 Veeresh S

Nov 24, 2018

Thank you Andrew NG for teaching AI

創建者 Srivathsan A

Nov 24, 2018

Awesome conclusion to deep learning. The 1 side trigger detection algorithm is good final touch. Thank you Andrew NG..

創建者 zhiqing h

Nov 24, 2018

Very detailed hands-on assignment. Hard tho

創建者 Brian L

Nov 26, 2018

This was an awesome sequence. I wanted to understand Deep Learning and the techniques and ideas that had advanced the state of the art beyond ordinary neural nets. I was particularly interested in Sequence Models which are of interest in my line of work.

創建者 Sushanta P

Dec 15, 2018

Andrew Ng at it best.

創建者 Mukund C

Dec 14, 2018

Best in the series

創建者 罗炜儒

Dec 14, 2018

该门课程对序列模型的讲解由浅入深,一步步带领我们从最基础的RNN走到最后的LSTM及更复杂的模型,作业十分有趣,尤其是课程最后一次作业能让我们真切感受到深度学习的力量及其给我们的作业

創建者 Michał K

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