Learner Reviews & Feedback for Structuring Machine Learning Projects by DeepLearning.AI
About the Course
Top reviews
YP
Jul 25, 2018
Very important and valuable intuitions about DNN training/optimization. It's full of really practical information while implementing my own models.DNN을 실제 적용할때 반드시 이해하고 적용해야 할 실질적 내용들로 구성된 멋진 코스 입니다!
TW
Jul 16, 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.
1401 - 1425 of 5,743 Reviews for Structuring Machine Learning Projects
By Kamal S
•Mar 24, 2018
This Course looked less important from the outside. Surprisingly gave me new ideas and cleared many misconceptions.
By Shaik A
•Feb 14, 2018
Very useful information. This course gave a chance to understand organize the neural networks and machine learning.
By Abin M A
•Feb 5, 2018
Very useful for beginners as this course explains many practical aspects techniques to approach real world problem.
By Karl H
•Feb 4, 2018
Very informative course. It would have been nice if there was an assignment on an application of transfer learning.
By Iman K
•Nov 20, 2017
best ML course. Hopefully we see more courses like this
. Maybe for specific problems or tools like tensorflow etc.
By Hamza A
•Aug 22, 2017
If you learn how to improve your machine learning applications efficiently, I highly recommend this course for you.
By claudia i r m
•Aug 28, 2022
A wonderful learning experience with great pedagogy and incredible concepts, applied through the labs and quizzes.
By kleber l
•Feb 15, 2021
This course although isn't code, it is useful, because, now I can guide my project towards a better path directed.
By Matthew N
•Feb 10, 2021
Andrew Ng is an awesome instructor on a very complex topic such as optimization and assessing models' performance.
By B V S A
•Aug 13, 2020
This is the most practical and well explained course on Deep learning implementation that I have ever come across.
By Dawood I
•Jun 9, 2020
Absolutely brilliant. What people learn after working on deep learning for years, Andrew taught us in this course.
By Manmohan K
•Jun 5, 2020
Gained good insight into the practical aspects of DL through this course and how to go about doing Error Analysis.
By Lakshya J
•Jun 2, 2020
Very practical and insightful course. I am sure these concepts will really help me when building my own ML systems
By Taiki O
•May 3, 2020
That was clear! However, some videos was ill-paced or I guess there was something wrong with the speed of videos.
By Hind A b
•Mar 7, 2020
very sightful course, i learned how to work on machine learning projects and how to analyse errors in development.
By Renato L R
•Jan 9, 2020
Very useful training that provides additional insights for a better plan and result's analysis of your ML projects
By Igor _
•Sep 12, 2019
This was the most useful course from the first three courses in this specialty; looking forward what will be next
By Rongyao W
•Aug 18, 2019
Great hands on experience with deep learning. It surely help a lot for building insight what deep learning can do.
By Jason D
•Aug 10, 2019
Good course to build up your knowledge on how to go about structuring machine learning projects in the real world.
By Hiren K
•Jul 29, 2019
Very interesting and informative course. Professor Ng was quite good at teaching complex phenomena in an easy way.
By Jonathan M
•Jul 25, 2019
Great course that shows you many different concepts and how you can approach different problems you may encounter.
By Paul H C
•Oct 8, 2018
This is so useful!!! I know now what to do when I blocked: keep iterating: start quickly and iterate until success
By David B
•Sep 9, 2018
Invaluable if you are implementing a project, which is, I guess, what we must do to fully understand the concepts.
By Leon G
•Jul 1, 2018
Abundant practical, industrial-level advice on ML projects and their improvements. Awesome course, awesome Andrew.
By Rodolfo C
•Apr 7, 2018
Good review of the machine learning mentality and how things can be simplified when using this kind of strategies.