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

4.8
stars
49,658 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

ED

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.

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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5176 - 5200 of 5,692 Reviews for Structuring Machine Learning Projects

By Ed G

•

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

By Shriniwas S U

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May 2, 2020

Satisfied with course. Thank u Instructor

By Hamidreza C

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Jan 7, 2020

Good course, nice case studies, liked it.

By Gaurav A

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Aug 26, 2019

Great course, good structure, nice theory

By Akansha B

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Aug 3, 2020

Was good as an intro could be hands on..

By David A

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Nov 19, 2018

Didn't get any practice coding sessions.

By Yunfei D

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Mar 5, 2018

Why is there no programming assignments?

By John K

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Sep 19, 2017

I would have liked more hands o examples

By Zhen L

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Sep 9, 2017

Provide many suggestions about practice.

By Michael F

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Apr 20, 2018

I would have liked more coding modules.

By anusha b

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Mar 12, 2018

It was actually very nice and intuitive