Learner Reviews & Feedback for Structuring Machine Learning Projects by DeepLearning.AI
About the Course
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 m...
Top reviews
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.
JB
Jul 2, 2020
While the information from this course was awesome I would've liked some hand on projects to get the information running. Nonetheless, the two simulation task were the best (more would've been neat!).
5001 - 5025 of 5,736 Reviews for Structuring Machine Learning Projects
By Yang Z
•Oct 21, 2017
Some videos don't end properly and instead give you a black screen to stare at for a minute.
By Akhtar H
•Feb 10, 2021
This is little bit tricky course. But main understanding comes when you solve case studies.
By Neel K
•Oct 19, 2020
It was better to include some more case studies. This was a better real-time understanding.
By Michael L
•Jun 10, 2020
Sometimes, the explanations/advices given were too lengthly and contained some repetitions.
By Amielle D
•Jul 24, 2019
There were some typos throughout the course, but the core topics were still discussed well.
By Tariq A
•Jan 12, 2019
A good quality course, would have loved to have some programming exercises to go with this.
By Ankur K
•Nov 13, 2017
It would have been a little better if some assignments were also provided with this course.
By h_st
•Aug 1, 2021
It was really nice. Maybe some more hints could be given. I missed my own programming ;-)
By Rohini H
•Jun 10, 2020
still with some more example & more simplest way to solve them .with simple basic examples
By Martin B
•Mar 17, 2018
Again, excellent, but proof reading of the test and proof-viewing of the videos is needed.
By Sudeep K
•Apr 8, 2020
It could be more detailed. More Code intense! However, the course was really informative.
By Abhishek P
•Sep 24, 2019
Initially a bit hard to understand but repeating the session helped to grasp the concepts
By Pedro L A V
•Feb 26, 2018
Good course, but there are too many small topics in each week and no hands-on assignment.
By Blake C
•Sep 20, 2017
Not quite sure, but there are some problems in exam. Hopely fix them as soon as possible.
By Bharat M
•Jul 24, 2020
A good theoretical course to help remember the nuances of how to structure a ML project.
By Vikas C
•Jun 20, 2019
It was a nice course, it can better if some demo codes are used as an example separately
By Shuo W
•Jan 3, 2018
Pro: useful practical suggestions;
Con: language used in quiz should be further polished.
By Ridvan S
•Oct 15, 2017
"Chillout course", but "test-by-real-cases" is very exiting and very fine idea. Strong 4
By riad s
•Sep 21, 2017
I wish there was some practice assignments related to the concepts learnt in this course
By Vinay K
•Feb 5, 2020
Info about the approach in applying DL/ML concepts to various scenarios were explained.
By Vishal G
•Dec 19, 2019
Interesting course, but all this could have been summarised in the first course itself!
By Hao W
•Jun 17, 2019
This course is not so well organized as the previous two. Everything else is very good!
By donato t
•Jun 15, 2019
Very valuable insight in real world usage of DL and guidance in approaching DL projects
By Wilson L
•Sep 16, 2017
It would be even better if there are more quiz and assignments made in ipython notebook
By Eugene K
•Jul 17, 2023
Not a necessary course in my opinion. His other courses in this series is much better.