Chevron Left
Back to Structuring Machine Learning Projects

Learner Reviews & Feedback for Structuring Machine Learning Projects by deeplearning.ai

4.8
28,699 ratings
3,029 reviews

About the Course

You will learn how to build a successful machine learning project. If you aspire to be a technical leader in AI, and know how to set direction for your team's work, this course will show you how. Much of this content has never been taught elsewhere, and is drawn from my experience building and shipping many deep learning products. This course also has two "flight simulators" that let you practice decision-making as a machine learning project leader. This provides "industry experience" that you might otherwise get only after years of ML work experience. After 2 weeks, you will: - Understand how to diagnose errors in a machine learning system, and - Be able to prioritize the most promising directions for reducing error - Understand complex ML settings, such as mismatched training/test sets, and comparing to and/or surpassing human-level performance - Know how to apply end-to-end learning, transfer learning, and multi-task learning I've seen teams waste months or years through not understanding the principles taught in this course. I hope this two week course will save you months of time. This is a standalone course, and you can take this so long as you have basic machine learning knowledge. This is the third course in the Deep Learning Specialization....

Top reviews

AM

Nov 23, 2017

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

WG

Mar 19, 2019

Though it might not seem imminently useful, the course notes I've referred back to the most come from this class. This course is could be summarized as a machine learning master giving useful advice.

Filter by:

1 - 25 of 3,041 Reviews for Structuring Machine Learning Projects

By Liu H

Jun 11, 2019

This course would be immensely helpful for those who have not started on their first machine learning project. However, the insights shared are quite commonsensical and intuitive for those who have already had some minimal experience in machine learning. This course also does not feel as substantial as the other courses in the specialization, though the tips provided are definitely valuable.

By ABHISHEK K

May 31, 2019

I recommend this course. This will be a bit of theoretical which is good. It will talk about real world scenarios over the errors which is what we deal in day-to-day life and how to deal with it.

By Nazarii N

May 25, 2019

more practice!

By Walter G

Mar 19, 2019

Though it might not seem imminently useful, the course notes I've referred back to the most come from this class. This course is could be summarized as a machine learning master giving useful advice.

By Matei I

Feb 16, 2019

I'm glad I spent some time on the "Flight simulator" assignments in this course. It's the first time in the specialization when I actually found the quiz questions challenging, and that's a welcome change. However, I didn't learn too much from the lectures. They were too repetitive, either repeating themselves or the material from the previous course. One or two videos could also do with better editing work: I could hear Andrew making a soundcheck, and there's a 30sec segment that's played twice in a row. Overall, it's probably worth doing this course, given that it requires very little time, and the assignments are useful.

By THAMMANA S R

Sep 22, 2018

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.

By Ziping Z

Apr 07, 2018

A lot of concrete examples, including those in the lectures and in the tests. Gained some thoughts on how to manage a ML project. Thanks Andrew and deeplearning.ai for providing such a great course.

By ANKIT M

Nov 23, 2017

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

By Haci A K

Jul 17, 2019

good insights, looks like reflecting years of experience, as promised -)

By Antony W

Jul 17, 2019

I am glad I took this class. There are a lot of things think about with respect to structuring your M/L project. Fortunately, it is not as mysterious as people often claim...but it is very nuanced.

By Ranjan D

Jul 17, 2019

Great explanation on how to structure your machine learning projects like distributing data among train & dev/test set then what to do for each type of errors to continues to transfer learning, Multi task learning, End-to-End Deep learning. It has been a fantastic journey learning about these different techniques.

By Rochana C

Jul 16, 2019

Excellent simulator quizzes!

By Christos-Angelos V

Jul 16, 2019

Another great course by Coursera. Thank you very much for sharing this knowledge.

By Jingyu Z

Jul 16, 2019

many useful strategies can adopt to solve problems. really amazing course!

By Yuhang L

Jul 15, 2019

Very helpful. I have learned a lot about higher-level ideas of machine leaning / predictive modeling.

By daniele r

Jul 15, 2019

Good for the numerous hints about practical issues such as different distributions on train/dev/set. Very bad for the lack of hands-on assignments. Good practical advices but no occasion to see them working!

By Ishmael M

Jul 15, 2019

V

By Mostafa G

Jul 15, 2019

Great lecture on administering deep learning projects

By Martin R

Jul 15, 2019

Very heplful tips included in this course!

By amin n s

Jul 14, 2019

This course is unique in content and you cant find anything like it anywhere else.

The amount of experience that Andrew conveys is enormous and practical tips that only can come from a real professional like Andrew.

By Sumedh K

Jul 14, 2019

Amazing tips and tricks to fine tune and improve the Machine Learning models. And as always Andrew Ng does not disappoint.

By William G

Jul 14, 2019

not as technical as the first 2 courses in this specialization (and the next 2 for that matter), but it is still a well rounded course and highly recommend to do all the courses in this specialization!

By Arnav B

Jul 13, 2019

thank you Andrew Ng

By Julian O G

Jul 13, 2019

Conocimiento muy útil para estructurar proyectos de machine learning

By Kaan A

Jul 13, 2019

It was real fun. I've completed the first three course of the specialization looking forward to start fourth one.