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学生对 deeplearning.ai 提供的 Sequence Models 的评价和反馈

4.8
27,028 个评分
3,214 条评论

课程概述

In the fifth course of the Deep Learning Specialization, you will become familiar with sequence models and their exciting applications such as speech recognition, music synthesis, chatbots, machine translation, natural language processing (NLP), and more. By the end, you will be able to build and train Recurrent Neural Networks (RNNs) and commonly-used variants such as GRUs and LSTMs; apply RNNs to Character-level Language Modeling; gain experience with natural language processing and Word Embeddings; and use HuggingFace tokenizers and transformer models to solve different NLP tasks such as NER and Question Answering. The Deep Learning Specialization is a foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to take the definitive step in the world of AI by helping you gain the knowledge and skills to level up your career....

热门审阅

AM
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.

MH
Apr 21, 2020

Very good. I have no complaints. I though instruction was very clear. Assignments were very helpful and challenging enough that I learned something, but not so challenging that I got stuck too often.

筛选依据:

3051 - Sequence Models 的 3075 个评论(共 3,209 个)

创建者 Aswin R

May 22, 2020

Course contents were very good, but the assignments could have been improved a lot. Couldn't get much value out of the assignments rather than blindly following the instructions.

创建者 jie y

Mar 31, 2018

The class covered too less on the Sequence models such as LSTM and GRU. It has too much domain knowledge related videos. Also, it does not have any video related to Time Series.

创建者 Daniel H

Jul 18, 2020

The videos are good, however the assignments are too long with sooooo many text inside. You have to make it more efficient somehow.

But thank you anyway for the great content!

创建者 Touqeer A

Aug 9, 2020

Assignments in this course are relatively less organized. You have to read a lot of description first and then code and have to go back/forth between code and description.

创建者 Daniel E

Jul 12, 2018

I believe that the course needs more time allocated to the incremental teaching of this rather large subject area with varied applications. Just needs to be a better way.

创建者 Loic R W

Sep 26, 2019

The course was especially interesting in week 2 and 3, but the assignments for week 1 were confusing and sometimes it was hard to follow where the logic was coming from.

创建者 Aditya D

Aug 24, 2020

This was the most difficult to understand course in the whole specialization. Would have enjoyed more if the course material was a little more spaced and elaborated on.

创建者 Дмитрий П

Apr 9, 2018

Practical Assignments with Keras wasn't motivating. I spend more time to deep into the Keras rather than into the course topic. I prefer them to be using TF or Python.

创建者 许晶鑫

Jun 11, 2018

The supports in keras programming was so poor, that I could not quite understand each step. And the server was horrible, always got 405 response when saving my codes.

创建者 Joseph G B

Jun 9, 2020

This course should be broken into 4 weeks and spend more time building skills with Keras. The number of hours listed next to each assignment is unrealistically low.

创建者 赵凌乔

Sep 20, 2019

The lecture was great but the errors in the programming assignment (especially in formal-typed formulas) really wasted a lot of time and make me confusing at first.

创建者 Sebastian S

Mar 14, 2019

The ideas presented here were clear, however I found the programming assignments non-intuitive and not practical. I spent on them way more time than I wish i had.

创建者 Fernando A G

Jul 27, 2018

I enjoyed all the courses, from my personal point of view this course was not that fun as the other courses. Except for the trigger assignment it was awesome!

创建者 Zhao H

Jul 6, 2018

Too much was given in external python code for the first week's assignment (that should be learnt by us): not a good thing for us to gain a good understanding

创建者 Matias A

Aug 11, 2020

Worst course of the specialization, content is interesting and Andrew keeps explaining really well but programming assignments are clearly of a lower quality

创建者 Max W

Sep 7, 2018

The course is great but the tasks in Keras are too complex without background knowledge. Therefore, a reasonable introduction in Keras would be desirable.

创建者 Eymard P

Jul 31, 2018

Far less detailed than the other ones. The programming assignements are less interesting too, as a great part of the work consist of reading documentation

创建者 Reetu H

Dec 23, 2019

There were lot of bugs in the assignments taking up lot of time to fix. The course was okay, I liked the other courses in the specialization more.

创建者 Kaupo V

May 7, 2018

The Keras programming exercises are quite weak. Please re-think how to teach them more systematically. Currently it is quite a lot of hit and miss.

创建者 Prut S

Aug 15, 2021

The lectures were great, but the programming assignments could have been structured better, especially the final assignment which drove me nuts.

创建者 Assa E

Feb 10, 2021

That was much harder than the previous courses of the specialization. However it felt like the videos are more hasty and less understoodable

创建者 Leandro A

Mar 18, 2018

There was a bug in a programming assignment notebook that took too much time to notice that i was doing ok but the expected ouptut was wrong

创建者 David H P

Apr 2, 2018

The programming assignments required some extra effort to understand Keras which I thought may need an introduction video like tensorflow.

创建者 Iván V P

Feb 18, 2018

Several grader issues, only 3 weeks of work, and a lot of errors in the solutions... In addition, less content than in the other courses...

创建者 Rishabh G

Sep 19, 2020

The earlier courses were easy to understand, however, this was way too difficult. Andrew Ng did not make this easy like the other courses.