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

4.8
stars
47,499 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

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!).

AM
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.

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5176 - 5200 of 5,408 Reviews for Structuring Machine Learning Projects

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 Jean-Michel P

Jun 29, 2021

I feel like this course should be broken down and included in the other courses to get better context within these other courses.

By sai r t

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.

By David P

Oct 17, 2017

Not nearly as good as the first two courses. These two weeks should probably be added into the second course at some point...

By Oliver O

Oct 16, 2017

Would like more applied discussion and for it to be Longer. In particular I would like to see a discussion on class imbalance.

By Shuai W

Sep 19, 2017

The content of this course is a bit too little for me.

However, it provides useful guidance for my projects. Much appreciated!

By Gary S

Sep 15, 2017

Not nearly as valuable as the first Deep Learning course. And the questions posed in the quizzes seemed far more subjective.

By Pejman M

Oct 21, 2017

Programming practices with TensorFlow should have continued in this course. Unfortunately, these two weeks were all talking.

By Nithin V

Jan 3, 2021

Need more quizzes, assignments to deepen the understanding, But otherwise thank you Andrew Ng for presenting this material

By Panos K

Apr 18, 2021

The pace of the first part of the course was too slow. The second part (from Transfer learning onwards) was much better.

By Mustafa H

Jul 16, 2018

This course does discuss interesting and important subjects but I feel it can be combined with course 2 of this series

By Ahmed A

Jul 10, 2018

course is very good have a lot of important theory, it will be amazing if become 3 weeks with programming assignments.

By Kevin Q

Mar 19, 2018

lot of issues with assignments and ambiguous quiz questions this time around, not as polished as other Andrew courses