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

4.8
stars
49,925 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

TG

Dec 1, 2020

I learned so many things in this module. I learned that how to do error analysis and different kind of the learning techniques. Thanks Professor Andrew Ng to provide such a valuable and updated stuff.

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.

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5126 - 5150 of 5,724 Reviews for Structuring Machine Learning Projects

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.

By Sathiraju E

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May 25, 2019

Thank you, Andrew.

This course was very helpful though theory.

By Daniel Z

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Aug 14, 2018

Good course. It would be better with programming assignments.

By Antonio H

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Jul 2, 2018

I could not do the flight simulator test, it was not working.

By Youjiang Y

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Jan 16, 2018

It will be really nice if there is assignment for this course

By Jeremy O

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Apr 19, 2021

Was hoping to get some insight into architectural decisions.

By Dioselin E B P

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Jan 13, 2021

It's much information for only a one questionnaire for week!

By zhang l

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Mar 16, 2020

Some of the questions in the quiz set seems a bit confusing.

By gayatri h

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Jun 4, 2019

It gives the idea about real life machine learning problems.

By David d V

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May 24, 2018

It would have been great to add some programming assignments

By Jeff O

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Sep 11, 2017

Good material, just wish it had more "labs" to work through.

By Juan C M S

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Jun 8, 2020

In some occasions it's been has a bit redundant information

By Pranav B

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Jan 30, 2020

Good Course for Beginners need more programming assignments

By Gil E B

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Jul 29, 2019

Good Course to learn production pipelines for practical use

By Fereydoon V

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Feb 2, 2018

Hope we had programming assignment for this course as well!

By Nandigama V

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Jan 3, 2018

Very good course, It should be last course in specilization

By Richard M

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Oct 14, 2020

Interesting ideas, but not as good structured as course 1.