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

4.8
stars
46,433 ratings
5,322 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

JB
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!).

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.

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5026 - 5050 of 5,265 Reviews for Structuring Machine Learning Projects

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 Hugo 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.

By Mayur S

May 25, 2020

The course material can be clubbed with existing courses. It would have been much more meaningful with some examples and hands-on assignments

By Rindra R

Oct 11, 2017

Covered important topics and real-world project considerations. However, the content and assignments are too short to make it a full course.

By Daniel K

Jun 25, 2020

This time it was not that well-structured than the previous courses. I thought we would learn how to structure step by step an ML project.

By José G

Apr 18, 2020

Lots of information, few knowledge

Change name to "Struc. Deep Learning Projects", all other forms of ML not considered, specially for P2.

By Eric K

Jul 21, 2018

Too much similar material to the prior course, and only two simple quizzes, no hands-on programming assignments like in earlier courses.

By Eric M

Oct 20, 2017

A fundamentally very good course with a few technical gltiches that can be easily corrected and some confusing elements to be clarified.

By Bongsang K

May 21, 2018

I think this lecture is important for every research scientist. However, there was no programming examples so I was confused sometimes.

By Michael L

May 1, 2018

No programming assignments or labs, so too much theory, and too little chance to put same into practice. Not a good value for my money.

By Max S

Dec 13, 2017

Still good but getting much sloppier. Bad editing of the videos, some exercises plain wrong and staff not reacting to forum posts, etc.

By Xiang L

Apr 26, 2021

This session might not be very helpful for people from different backgrounds such as non-industral level application of deep learning.

By Lars L

Dec 30, 2017

Course materials need some cleanup. Were a number of audio blips, in the video. Material was good but just didn't seem as polished.

By Nitin S

Jun 25, 2020

Decent learning. Though quite some stuff, I felt as repetitive and obvious.

I wish there was some programming exposure as well here

By Taavi K

Nov 29, 2017

Too short on its own (took half a day to go through the whole thing), could have been combined with Course 2 of the specialization.

By Raghu t D

Aug 6, 2018

this session was good it would be more better if they provided the code of them..so that we could be abke to learn more from them

By Denys G

Nov 23, 2017

Felt a bit rushed, each video was full of good tips but personally I think each video should have been a jupyternotebook instead.

By Massimo A

Nov 18, 2017

More theoretical than the other courses in the specialisation but still very high quality.

Short but with a lot of information.