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

4.8
stars
49,903 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.

JB

Jul 1, 2020

While the information from this course was awesome I would've liked some hand on projects to get the information running. Nonetheless, the two simulation task were the best (more would've been neat!).

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5101 - 5125 of 5,720 Reviews for Structuring Machine Learning Projects

By Michael B

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Apr 4, 2018

Well structured material - trigger the desire to know more and more

By yifeng z

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Feb 27, 2018

kind of lacking in practical assignment. only quiz seems not enough

By Roger F

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Dec 4, 2017

It would be great to get some explanations in regard to both tests.

By Shirley Z

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Nov 6, 2017

Could be more examples or coding assignments for transfer learning.

By chao L

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Sep 29, 2017

Distills the key and practical aspects of machine learning projects

By Chuyi H

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Jul 2, 2020

the knowledge is very relevant and the quiz is fun and challenging

By Tomás O

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Jun 19, 2019

Very useful intuitions, needs a little more of coding if possible.

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