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

4.8
stars
49,769 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

NI

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Awesome course as always. The course teaches real world practical aspects of how to get started and navigate in the real world projects. The guidelines are actual learnings from years of experience.

SV

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This is the knowledge in which we will get from lots of experience only, but the andrew has shared in this course which might help us in future by saving a lot of time through this course experience

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5176 - 5200 of 5,702 Reviews for Structuring Machine Learning Projects

By John H

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Aug 26, 2017

Is the flight simulator hw going to be added soon?

By Pat B

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Dec 8, 2019

Great course. I liked the compact, 2-week format.

By liu c

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Mar 17, 2018

A little bit abstract. But still very inspiring!

By Florian M

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Aug 24, 2017

Very interesting tools and ideas for applied ML.

By Nicholas N S

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Apr 28, 2021

There is so much noise in the explanation voice

By Jason G

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Nov 24, 2018

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

By Mark

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Oct 12, 2018

Great course. Needs deeper practical examples.

By Francis J

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Feb 25, 2018

A lot of insights rather than technical details

By Lukáš L

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Jan 7, 2018

Coding exercises would be great in this course.

By Mares B

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Nov 17, 2020

A little short, maybe more hands on exercises?

By Ed G

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Nov 8, 2020

Concise course with some interesting concepts.

By Tulip T

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Jul 23, 2019

Quite helpful when you start a new ML project.

By S V R

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Nov 4, 2018

The session were simple, could be more complex

By Caique D S C

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Jul 30, 2018

very good course, could be less massive though

By Ivan V

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Dec 11, 2019

I want a program exercise like in 1-2 courses

By Dionysios S

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Nov 30, 2018

I would like to see more practice assessments

By Luis E R

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Jul 31, 2019

Very useful concepts that few people address

By Jun P

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Apr 22, 2018

Kind of boring than the cnn and rnn class ..

By John H

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Aug 29, 2017

Useful content, could be much more succinct.

By vijaykumar

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May 15, 2020

This course is awesome and good knowledge .

By Alfredo M

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Mar 14, 2018

There were no practical coding homeworks :(

By Igor C

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Feb 14, 2018

A little less dense than the other courses.

By Rajesh M

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Oct 11, 2017

Can reduce some of the repetitive material

By JEROME D

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Sep 21, 2020

Maybe add 1 question at the end of videos

By Mr. S A

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Sep 12, 2020

a bit slow and no programming assignments