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

38,995 个评分
4,282 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....



Mar 31, 2020

It is very nice to have a very experienced deep learning practitioner showing you the "magic" of making DNN works. That is usually passed from Professor to graduate student, but is available here now.


Nov 23, 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.


3801 - Structuring Machine Learning Projects 的 3825 个评论(共 4,244 个)

创建者 Alejandro R V

Jan 08, 2018

Not as interesting as the others, I personally prefer math

创建者 Gopala V

Oct 24, 2017

Gave some ideas on mismatched data and how to address them

创建者 Akshita J

Apr 23, 2020

An assignment could have been included to let practically

创建者 Roberto J

Oct 19, 2017

A bit dry, would love to see some more concrete examples.

创建者 Vinicius B F

Oct 23, 2017

Content was fantastic, but the videos were badly edited.

创建者 Suresh P I

Sep 10, 2017

Can be potentially folded into other courses if possible

创建者 heykel

Jan 27, 2020

very helpful to build an intuition for DL strategies...

创建者 Rafael G M

Dec 07, 2019

Providing further references would benefit this section


Nov 15, 2017

You can know well a lot of strategy in machine learning

创建者 王毅

Dec 24, 2019

the content is good, but the videos are not well made.

创建者 Shuochen Z

Feb 18, 2019


创建者 Gundreddy L M

Sep 11, 2018

excerice should be given for this one proper user case

创建者 Alexey S

Oct 23, 2017

Good class, but 2 previous are much better and useful.

创建者 Lei C

Sep 25, 2017

the answer of the assignment is a little bit arguable.


May 28, 2020

machine learning project are highly iterative as you.

创建者 diego s

Feb 18, 2020

I miss notebooks for practice, besides questionnaires

创建者 Xinghua J

Sep 06, 2019

If there is some coding practice, it would be better

创建者 Hee S K

Apr 18, 2018

It is an unique lecture providing empirical advises.

创建者 Pablo L

Oct 30, 2017

Great set of guidelines. Mostly theoretical, though.

创建者 Cristina G

Oct 22, 2017

Concrete reminders of important and practical points

创建者 Ktawut T

Oct 10, 2017

Very useful materials for leading a ML research team

创建者 awalin s

Sep 29, 2017

interesting insights about real world implementation

创建者 Yu L

Apr 03, 2020

would like to have more excercise related to coding

创建者 Mage K

Mar 07, 2018

Would've liked to have some programming assignments

创建者 Carlisle

Aug 20, 2017

Introduced a lot on engineering project experiences