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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.

TR

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This is a must course in the entire specialization. It covers the step by step procedure to approach and solve a problem. The case studies provided are real world problems which are so much helpful.

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5426 - 5450 of 5,708 Reviews for Structuring Machine Learning Projects

By Daniel C

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Nov 19, 2017

Not as helpful... just a few suggestions and ideas... but there's no great application of the information learned here like a walk-through project or something with code, that's graded.

By Luiz C

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Oct 22, 2017

less useful than previous courses.

Would appreciate to go much deeper in directions like CNN, RNN, RL and review Unsupervised Learning (which was too light, ... no mention about RBM)

By Akshay S

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Jun 18, 2020

It was very theoretical and subjective.

It would be useful if the learner has some more experience in DNN than currently expected.

But I definitely enjoyed 2nd week of the course.

By Andrew C

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Oct 29, 2017

Interesting content, but lacking in real work. As with all of the deeplearning.ai courses thus far, the multiple choice questions are frequently ambiguous and poorly worded.

By Zsolt K

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Sep 24, 2018

The information is really basic, most of it is self explanatory. This shouldn't be a course on its own, rather maybe a week/half weeks worth of material in another course.

By Sherif A

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Nov 25, 2017

This course is too subjective. Andrew shares his experience in a structured way in the lecture. However, I feel that correct structuring decisions need to be brainstormed.

By Hieu N

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Jan 15, 2024

Many useful tips but it's hard to remember. I think they'll become useful when I start building these voice/image recognition systems since I'm terrible at memorization.

By Patrick F

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Dec 12, 2019

Seeing different practical use scenarios and adaptions is fine but it got pretty boring without a real application to tune. The Quizzes on the other hand were very good!

By Alberto S

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May 29, 2018

Although everything taught is relevant, it was too much theoretical. And some of the evaluation questions are not clear (well, at least for non native English speakers).

By Daniel V

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Feb 26, 2020

Generally useful skills, but the contents partially overlap with previous courses and the overall quality doesn't match the previous courses (eg poor video mastering).

By Davide C

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Nov 26, 2017

The course was interesting, but in my opinion too theoretical. I preferred the first 2 courses with Python programming. I am now looking forward to the next 2 courses.

By Felipe L d S

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Jun 7, 2018

Even though some of the content is useful, I feel like this course should be merged with the second one. There is not new information enough to justify a new course.

By Thomas J

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Jan 24, 2018

Good material was presented in this course but there were a number of technical errors in the video recordings. If they were cleaned up this course would be perfect.

By Jose P

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Sep 30, 2019

Topics are a bit vague, which is fine as the content is interesting and useful nonetheless, but perhaps exposition is too lengthy relative to the amount of content.

By Robbin R

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Feb 17, 2018

Gives good insights on how to work on a Machine Learning project yet. Provides some rule of thumbs for different hick-ups that may be encountered during a project.

By Nick S

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Sep 8, 2017

even though there are great tips and advices, it does not justify an entire course and they can be mentioned in 3 videos so a lot of the videos were repetitive.

By Kan X

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Feb 18, 2020

I like this specialization in general. However, this third one has too many overlapping contents and some videos are not that useful. Just personal opinion.

By Jkernec

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Dec 23, 2017

Homework is lacking. It is too easy to pass. I feel like the programming task or homework task fell short. The lectures were good but too little practice.

By Hanbo L

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Sep 22, 2019

Good non-technical materials, but short enough to be incorporated into other courses. Some aspects feel subjective. Many typos/minor mistakes in quizzes

By vincent p

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Aug 24, 2019

Was really enthousiastic about the first two courses in the specialization, the third however felt a bit like going back a step in level of advancement.

By Molo M

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May 6, 2022

It is a good course and gives a lot of good advice. However, it would be good if there was a practical project to practice everything that was taught.

By Rishabh G

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May 22, 2020

A different course for only two weeks of content? This is nuts. I waited for 15 days for financial aid to be approved and I completed it within 5 days.

By Leitner C S E S

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Sep 15, 2017

Only interesting if you don't have much experience with machine learning; Might or might not be great if you are a novice, though - hard to say for me.

By Deleted A

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Oct 14, 2017

There was some very valuable material. However, I think some of the videos could have been prepared a little bit better and could do with more editing

By Carsten F

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Jan 30, 2018

Course was less interesting than the other parts. Also very negative that the last part of the 5-part specialization is taking ages to be finalized.