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

4.8
stars
49,614 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.

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.

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4701 - 4725 of 5,688 Reviews for Structuring Machine Learning Projects

By Grant G

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Dec 3, 2017

A pleasant diversion into practical considerations of project design. However the lack of programming assignments and the somewhat vague and fiddly quizzes make this a less satisfying course than it could have been.

By Jeffrey D

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Mar 31, 2020

This was a good overview of the concepts I have already learned. It was a good refresher on progress and changes in training best practices. There are a few flawed questions in both quizzes that need to be fixed.

By gjycoursera

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Jun 27, 2020

from my perspective, maybe, it would be better if this course is the end course of the specialization. the contents are greate. I would like to suggest others to put this course in the end of the specialization.

By Othman B

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Jan 2, 2018

Very interesting, but too short. The aim of the course is to provide a good overview of the different situations occuring in a project, but there is more questions arising. Experience will come with training.

By Chris M

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Dec 14, 2021

The information is very useful, but the text, quizzes, and video all felt a little less polished than the previous two courses. Not a big deal, but it was notable and occasionally distracted from learning.

By Antti R

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Nov 3, 2019

nice to follow, but I would have liked it there would have been more variance. e.g. quizzes breaking the videos. I'm basically comparing this experiment with the other courses made by Andrew/deeplearning.ai

By Samuel C

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Oct 14, 2018

A useful few hours of videos. I found the questions quite useful, but overall feel this project would have been better off being spread across other weeks, as it doesnt work so well as a stand-alone course.

By sam h

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Oct 21, 2017

Very practical. programing assignment using the concepts would help to solidify the concepts. I would really appreciate programming assignments on Transfer learning since a lot of industries practices it.

By Wiebe V

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Aug 30, 2018

Clear course, it would have been helpful to add notebooks to the course to have a more realistic feeling of the problems. This would make it also more clear how the dev set influences the training phase.

By Sandeep P

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Jun 24, 2018

The course appraises the reader of the various tricks that are needed to design nice machine learning projects. One minor suggestion would be to have some programming assignments for this course as well!

By Ed E

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Nov 6, 2017

Great material but a few glitches in the videos that need editing out. I'm sure the people responsible will put it right soon though; the course hasn't been out long. Part of an excellent specialisation.

By Jon-pierre H

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Nov 29, 2017

Overall the course was good, but lacked some minor information needed for the quizzes. The quizzes also included some questions that felt like they were meant to trick us rather than test our knowledge.

By Gregory B

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May 12, 2023

Lots of good information, and it's quick, but the course videos could use a bit of editing compared to the other ones. It's common to have repeated takes in the videos that should have been edited out.

By Summer Y

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Oct 2, 2017

I didn't find this course as useful as the previous two. I'd still recommend the course because some interesting concepts are covered. The materials seem more intuitive. The quizzes are good practices!

By Noam S

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Oct 16, 2018

The course is very teaching in my uneducated opinion and will help m later in life, hopefully.

I wish the test question had been more coherent.

I enjoyed learning it, and the simulator is a great idea!

By Maciej B

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Aug 25, 2017

Course is great although only in one case we have pdf's with additional lecture notes. They are more useful than ppt slides therefore it would be desirable to have them in other parts of the course

By Fayruj F S

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Sep 17, 2020

The course is perfect. But it would have been better if some ways implementation was also introduced to us. But overall Andrew is really helpful to make us visualize and understand new strategies.

By Yan

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Apr 15, 2019

In this section, only strategies discussed and no programming practice. So I don't think I really understand those tricks. Maybe when I enroll in real projects, those magic will show their powers.

By HongZhang

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Jun 21, 2018

Very good lessons to teach the principle of how to set up a machine learning project. Lots of tricks are taught, but still hoping there could be some practical assignment to enhance the knowledge.

By Oge M

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Sep 13, 2017

Videos could be shorter and better edited. Supporting materials could be better. Homework assignments were tedious and included rather confusing (and borderline tricky) questions and alternatives.

By João A J d S

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Jun 14, 2019

It is a useful Content to keep in mind. Not as practical as other contents in the Specialisation. But, as Andrew Ng pointed out, it is a topic many times overlooked and I'm glad it was discussed.

By Rahul K

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Jul 18, 2018

The course is the best available on the online education platforms so far. An excellent instructor and really engaging assignments. You get it all but it lacks availability or reading materials.

By Vaddadi S R

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Apr 15, 2020

Lot of things to intake , Error analysis seemed more difficult to me compared to Bias/Variance Analysis. I think lot of practice is required to really remember and apply in real world problems.

By mitch d

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May 5, 2018

There are some answers on the "flight simulator" that are ambiguously worded, and one that seems to flat-out contradict what Prof. Ng said in lecture. Search the discussion forums for "foggy".

By Eric v d K

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Dec 28, 2017

Loved the course, and the simulation was great. Doing an actual transfer learning programming exercise in TensorFlow could be an awesome addition.

Best & thanks again for an awesome course!

Eric