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学生对 提供的 Structuring Machine Learning Projects 的评价和反馈

45,369 个评分
5,170 条评论


You will learn how to build a successful machine learning project. If you aspire to be a technical leader in AI, and know how to set direction for your team's work, this course will show you how. Much of this content has never been taught elsewhere, and is drawn from my experience building and shipping many deep learning products. This course also has two "flight simulators" that let you practice decision-making as a machine learning project leader. This provides "industry experience" that you might otherwise get only after years of ML work experience. After 2 weeks, you will: - Understand how to diagnose errors in a machine learning system, and - Be able to prioritize the most promising directions for reducing error - Understand complex ML settings, such as mismatched training/test sets, and comparing to and/or surpassing human-level performance - Know how to apply end-to-end learning, transfer learning, and multi-task learning I've seen teams waste months or years through not understanding the principles taught in this course. I hope this two week course will save you months of time. This is a standalone course, and you can take this so long as you have basic machine learning knowledge. This is the third course in the Deep Learning Specialization....


Nov 22, 2017

I learned so many things in this module. I learned that how to do error analysys and different kind of the learning techniques. Thanks Professor Andrew Ng to provide such a valuable and updated stuff.

Dec 1, 2020

I learned so many things in this module. I learned that how to do error analysis and different kind of the learning techniques. Thanks Professor Andrew Ng to provide such a valuable and updated stuff.


4776 - Structuring Machine Learning Projects 的 4800 个评论(共 5,113 个)

创建者 Luis A P

Jul 2, 2020

very nice

创建者 Yechan K

Jun 17, 2020



Apr 5, 2018

Thank you

创建者 Abhijeet R P

Oct 18, 2017

Great! :)

创建者 舒意恒

Oct 14, 2017

very nice

创建者 TianPing

Aug 27, 2017


创建者 Dave

Jul 9, 2020


创建者 Yashika S

Sep 27, 2019

good one

创建者 Xiong Z

Sep 3, 2019


创建者 M N N

May 28, 2019


创建者 mingwei Z

Sep 6, 2018

so well

创建者 靳雅麟

Dec 23, 2017


创建者 Tất T V

Oct 15, 2017


创建者 Takuya Kudo

Aug 10, 2019


创建者 Riyaz A

Sep 22, 2017







Oct 30, 2020


创建者 akash k

Aug 13, 2020


创建者 Alaa E B

Jun 23, 2020


创建者 CK P D

May 2, 2020


创建者 Annaluru K

Apr 17, 2020



Oct 23, 2019


创建者 zhesihuang

Mar 3, 2019



Jul 8, 2018


创建者 Felix E

Oct 9, 2017

This is a 2-week follow-up on the previous two courses in this specialization.

While it's a decent course that goes over a few interesting topics, I have a hard time giving it more than three stars. Reasons for that are below:

(1) Especially the first week felt very slow and repetitive. Most of the material could have been summarized a much smaller timeframe.

(2) The course went over some interesting topics in a very high-level way, but skipped a lot of the details that would have been very interesting to people looking to learn deep learning in depth (like the target audience of this course!).

(3) While I think the approach of having some themed case studies for the test is neat, a lot of the answers left me thinking "well, the correct answer would also depend on X which isn't specified". Good concept to test knowledge in a "discussion/oral exam" session, but IMHO bad for hard "wrong or right" multiple choice tests.

(4) Some videos had "black screen" times at the end, errors, cut-offs and repetitions were not cut out, and overall I think this had the least amount of "polishing" of the courses in this specialization so far.

I'd have preferred if the content of this course were a bit more steamlined and merged it into the other courses of this specialization.

创建者 Aristotelis-Angelos P

Jul 6, 2018

Overall, I think that it was a good course but in my opinion, the knowledge of this course cannot be easily transferred to people with very few experience in Machine Learning. Therefore, I was wondering whether it should be the 3rd course or the 5th course in this Deep Learning Specialization! Moreover, in order for someone to deeply comprehend these concepts such that he/she is able to apply them in a Machine Learning project, he/she should work on a project on his own where he/she will meet these concepts and will have to search in order to solve them.Last, personally, even though I am quite satisfied from the courses, I would expect that one more course is added to Coursera which is going to require to build a Deep Learning project! I think that this course should be of more advanced level and require (not Intermediate as those ones) and should require from students to build projects like the ones builded in the cs230 class from Stanford.Greetings from a PhD USC student