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Learner Reviews & Feedback for Structuring Machine Learning Projects by DeepLearning.AI

4.8
stars
47,503 ratings
5,446 reviews

About the Course

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....

Top reviews

MG
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.

TG
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.

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5151 - 5175 of 5,411 Reviews for Structuring Machine Learning Projects

By Patrick F

Dec 12, 2019

Seeing different practical use scenarios and adaptions is fine but it got pretty boring without a real application to tune. The Quizzes on the other hand were very good!

By Alberto S

May 29, 2018

Although everything taught is relevant, it was too much theoretical. And some of the evaluation questions are not clear (well, at least for non native English speakers).

By Daniel V

Feb 26, 2020

Generally useful skills, but the contents partially overlap with previous courses and the overall quality doesn't match the previous courses (eg poor video mastering).

By Davide C

Nov 26, 2017

The course was interesting, but in my opinion too theoretical. I preferred the first 2 courses with Python programming. I am now looking forward to the next 2 courses.

By Felipe L d S

Jun 7, 2018

Even though some of the content is useful, I feel like this course should be merged with the second one. There is not new information enough to justify a new course.

By Thomas J

Jan 24, 2018

Good material was presented in this course but there were a number of technical errors in the video recordings. If they were cleaned up this course would be perfect.

By Jose P

Sep 30, 2019

Topics are a bit vague, which is fine as the content is interesting and useful nonetheless, but perhaps exposition is too lengthy relative to the amount of content.

By Robbin R

Feb 17, 2018

Gives good insights on how to work on a Machine Learning project yet. Provides some rule of thumbs for different hick-ups that may be encountered during a project.

By Nick S

Sep 8, 2017

even though there are great tips and advices, it does not justify an entire course and they can be mentioned in 3 videos so a lot of the videos were repetitive.

By Kan X

Feb 18, 2020

I like this specialization in general. However, this third one has too many overlapping contents and some videos are not that useful. Just personal opinion.

By Jkernec

Dec 23, 2017

Homework is lacking. It is too easy to pass. I feel like the programming task or homework task fell short. The lectures were good but too little practice.

By Hanbo L

Sep 22, 2019

Good non-technical materials, but short enough to be incorporated into other courses. Some aspects feel subjective. Many typos/minor mistakes in quizzes

By vincent p

Aug 24, 2019

Was really enthousiastic about the first two courses in the specialization, the third however felt a bit like going back a step in level of advancement.

By Rishabh G

May 22, 2020

A different course for only two weeks of content? This is nuts. I waited for 15 days for financial aid to be approved and I completed it within 5 days.

By Leitner C S E S

Sep 15, 2017

Only interesting if you don't have much experience with machine learning; Might or might not be great if you are a novice, though - hard to say for me.

By Deleted A

Oct 14, 2017

There was some very valuable material. However, I think some of the videos could have been prepared a little bit better and could do with more editing

By Carsten F

Jan 30, 2018

Course was less interesting than the other parts. Also very negative that the last part of the 5-part specialization is taking ages to be finalized.

By Dany J

Nov 15, 2017

Good content, but could definitely benefit from a more fleshed out problem to solve. The content beg for a larger concrete coding exercice project.

By John J

Apr 18, 2021

Appears to be some errors in the section titles (Flight Simulator??). Also, some parts didn't seem to be as polished as the previous two courses.

By Hernan J

Nov 2, 2020

It's easy and more simple than the others in specialization. Can be more deeper into ML project organization management. It's ok, could be better!

By Jordon B

Jan 31, 2018

This course did not contain programming assignments, only quizzes, and was thus considerably less useful, even though the knowledge was important.

By ccbttn

Oct 12, 2017

Quite some questions are confusing and some are not correct itself. and this course is more concept based, didn't actually get to program a lot.

By Giacomo A

Jan 28, 2018

Contains some useful tips, but they are a bit too diluted - I feel like it could have lasted much less and still conveyed the same information.

By Yancey S

Sep 25, 2018

This course provides some interesting insights into how to approach machine learning projects, but feels a little light on substance at times.

By Even G

Oct 20, 2017

Great content. Some strange audio that I think should've been cut (especially in week 2). I suspect the week 2 quiz is a little buggy as well.