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

49,733 ratings

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


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.


Aug 22, 2020

Excellent start for digging into topics that are not taught nowhere else. The author books 'Machine Learning Yearning' is a great next read that goes deeper in some of the aspects, really recommended.

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5176 - 5200 of 5,697 Reviews for Structuring Machine Learning Projects

By Jason G

Nov 24, 2018

Not as strong as the other 4 of 5 of the series

By Mark

Oct 12, 2018

Great course. Needs deeper practical examples.

By Francis J

Feb 25, 2018

A lot of insights rather than technical details

By Lukáš L

Jan 7, 2018

Coding exercises would be great in this course.

By Mares B

Nov 17, 2020

A little short, maybe more hands on exercises?

By Ed G

Nov 8, 2020

Concise course with some interesting concepts.

By Tulip T

Jul 23, 2019

Quite helpful when you start a new ML project.

By S V R

Nov 4, 2018

The session were simple, could be more complex

By Caique D S C

Jul 30, 2018

very good course, could be less massive though

By Ivan V

Dec 11, 2019

I want a program exercise like in 1-2 courses

By Dionysios S

Nov 30, 2018

I would like to see more practice assessments

By Luis E R

Jul 31, 2019

Very useful concepts that few people address

By Jun P

Apr 22, 2018

Kind of boring than the cnn and rnn class ..

By John H

Aug 29, 2017

Useful content, could be much more succinct.

By vijaykumar

May 15, 2020

This course is awesome and good knowledge .

By Alfredo M

Mar 14, 2018

There were no practical coding homeworks :(

By Igor C

Feb 14, 2018

A little less dense than the other courses.

By Rajesh M

Oct 11, 2017

Can reduce some of the repetitive material


Sep 21, 2020

Maybe add 1 question at the end of videos

By Mr. S A

Sep 12, 2020

a bit slow and no programming assignments

By Shriniwas S U

May 2, 2020

Satisfied with course. Thank u Instructor

By Hamidreza C

Jan 7, 2020

Good course, nice case studies, liked it.

By Gaurav A

Aug 26, 2019

Great course, good structure, nice theory

By Akansha B

Aug 3, 2020

Was good as an intro could be hands on..

By David A

Nov 19, 2018

Didn't get any practice coding sessions.