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

48,887 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


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.


Mar 30, 2020

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.

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2876 - 2900 of 5,576 Reviews for Structuring Machine Learning Projects

By Martha Y S V

Oct 16, 2017

Nice course, but I missed the python practice.

By Oleksandr M

Oct 14, 2017

Very useful tools and recommendations. Thanks!

By Huaizheng Z

Aug 25, 2017

Good for researcher to review basic knowledge.

By 陈啸

Aug 24, 2017

This course will help you avoid many mistakes.

By Masahiro M

May 4, 2021

Very practical with really good case studies.

By Maria R

Mar 21, 2021

Very easy to understand, ilustrative examples

By Chang X

Oct 27, 2020

thanks Andrew for the great course materials!

By Heidy E M N

Aug 11, 2020


By mayukh m

Apr 13, 2020

great case study approach to machine learning

By Christian D C H

Oct 15, 2019

Excellent practical advise by Prof. Andrew Ng

By Almir I

Mar 13, 2019

It's a great but short (2 weeks only) course!

By Qasid S

Feb 7, 2019

I haven't seen this type of guide on any Mooc

By Manuel F

Jan 10, 2019

Very valuable and practical insights. Thanks!

By Wadikur R

Dec 25, 2018

This course so essential and I learned a lot.


Sep 3, 2018

Great course content, could be longer though.

By Alice G

Jun 27, 2018

Very good lesson on more strategic approaches

By Kishan

Jun 18, 2018

Very pragmatic course for all data scientists

By Phailendra D

Apr 17, 2018

Very good course on structuring the projects.

By Jiaming H

Mar 19, 2018

Great Course. Better if have coding exercise.

By Aravinda G

Mar 17, 2018

Amazing course! Thank you very much Coursera!

By Julio

Mar 14, 2018

now, i have more general knowledge about this

By Cristian R M

Feb 20, 2018

Unique gold course for real projects in ML/DL

By Fabian S

Feb 10, 2018

very useful, recommend to every practitioner!

By Wei X

Feb 2, 2018

important practical knowledge for application


Nov 3, 2017

Many helpful experience. It really helped me.