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

4.8
stars
49,809 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

MG

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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.

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.

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5101 - 5125 of 5,708 Reviews for Structuring Machine Learning Projects

By Aniceto P M

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Apr 24, 2019

This course is a bit short but there i a lot of experience bottled

By Javier P

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Oct 19, 2017

Programming assignments for transfer learning would have been nice

By manish c

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Jan 29, 2020

Nice to learn skills about project handling in machine learning.

By Luis E G

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Dec 23, 2019

A little bit boring and repeated info., but still valuable stuff.

By Lili W

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Aug 19, 2018

Tooo much time to repeat boring things...but still a good lesson!

By Nicholas K

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May 13, 2018

Worthwhile: good info and the practical aspects of tuning models.

By Alexander B

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Apr 24, 2018

Good for understand how to spend your time on DL projects I guess

By Kunkyu L

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Sep 14, 2017

It's difficult for me, so I have to retake 3 course, when I need.

By harm l

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Sep 10, 2017

Theoretical insights in strategic development of your ML project.

By Ziyi H

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Nov 18, 2018

The answer of Questions from quiz 2 seems to be not so confident

By Mohit k

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Jun 29, 2018

Superbly discussed practical problems in the field of ML and DL.

By Ch N

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Sep 11, 2017

A programming assignment could be included to learn more better.

By Raimondo M P

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Apr 7, 2020

I would have liked some Python assignments on Transfer Learning

By Hamzah A

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Sep 7, 2019

It would be better to have some hands on assignment or quizzes.

By Mehmet N

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Jan 3, 2019

Some questions/answers of the quizzes were not accurate enough.

By Erik B

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May 4, 2018

Provides a more scientific approach into hyperparameter tuning.

By Qihang S

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Mar 25, 2018

I hope that in Course 3 there are some programming assignments.

By Ashwani K

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Apr 27, 2020

Nicely explained the concepts and importance of error analysis

By Su L

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Mar 15, 2020

Volumns of different vedios are different. Some are too small.

By Zhuo Y

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Feb 23, 2020

complementary material for the book "machine learning yarning"

By PANKAJ R

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Mar 12, 2018

Lot of theory was their. Good but felt asleep after some time.

By Wenhai Z

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Nov 27, 2017

I would wish there were more programming practice assignments.

By Kyle H

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Oct 22, 2017

Contained all good content, there just wasn't very much of it.

By Daniel L

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Sep 21, 2020

The course is so useful, but sometimes the voice turns so low

By Paweł P

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Oct 11, 2019

Good overview of the problems occuring while training models.