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

45,739 个评分
5,219 条评论


In the third course of the Deep Learning Specialization, you will learn how to build a successful machine learning project and get to practice decision-making as a machine learning project leader. By the end, you will be able to diagnose errors in a machine learning system; prioritize strategies for reducing errors; understand complex ML settings, such as mismatched training/test sets, and comparing to and/or surpassing human-level performance; and apply end-to-end learning, transfer learning, and multi-task learning. This is also a standalone course for learners who have basic machine learning knowledge. This course draws on Andrew Ng’s experience building and shipping many deep learning products. If you aspire to become a technical leader who can set the direction for an AI team, this course provides the "industry experience" that you might otherwise get only after years of ML work experience. The Deep Learning Specialization is our 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 gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI....


Mar 30, 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.

Jul 1, 2020

While the information from this course was awesome I would've liked some hand on projects to get the information running. Nonetheless, the two simulation task were the best (more would've been neat!).


4651 - Structuring Machine Learning Projects 的 4675 个评论(共 5,162 个)

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 22, 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 Hanqiu D

Jan 9, 2021

It's too easy and cannot be a reasonable single course.

创建者 heykel

Jan 27, 2020

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

创建者 Rafael G M

Dec 7, 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 B S K

Jul 14, 2020

Good teaching of practical approaches and nice quizzes

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 17, 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 22, 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.


Oct 6, 2020

Content is good. Presentation could have been better.

创建者 Kumari P

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 6, 2019

If there is some coding practice, it would be better

创建者 Pranjal V

Jul 11, 2020

Very well explained but needs more reading material.

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 F

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