AM
Nov 22, 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.
TG
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.
By Charles S
•Nov 28, 2017
Excellent lectures and notes as always. Great insights and clearly explained. I think we could have used a programming exercise on transfer learning at least in this section.
By Yusuf E B
•Jan 17, 2024
While the course content is very good just like the previous 2 courses of the specialization, quizzes on this course have little language errors that make the questions vague
By Akanksha D
•Jan 7, 2018
More coding exercises could be included with much more mathematics background explained. Videos could be made a little shorter. There is redundancy in the some of the videos.
By Juan M
•Jan 4, 2018
Good overview of how to structure ML projects with great practical advice. I wish the course had includes a programming lab to help us try out and practice some of the ideas
By Lê B Q T
•Nov 22, 2023
This course is pretty good. In this, I can learn about real world situation on developing machine learning projects. But I think, it could be better if has some code (Maybe)
By Aravindh V
•Aug 29, 2020
Good content. The tips and tricks a experienced AI practitioner has was shared. But at least one programing exercise applying all the concepts learnt, would have been great.
By Luis J P M
•Jan 12, 2020
In the first quiz, the comments about why an answer is correct are too simple. On the contrary, in the second quiz, the comments are really good and give us better feedback.
By Uddhav D
•Jun 2, 2019
I feel more Examples should be given regarding the variable and bais tuning, also Error analysis videos should be a bit in-depth. Everything else is as good as it can get :)
By Jean M A S
•Oct 27, 2017
The simulations were very good to build a good intuition about setting up a machine learning project.
But I regret that we didn't have coding exercises. 4 stars for this one.
By Carlos S C V
•Apr 15, 2020
Me gustó el curso, pero creo que algunas lecciones fueron un poco más largas de lo necesario. Debo agregar que me gustaron mucho los simuladores, creo que me ayudaron mucho
By Vinod S
•Nov 19, 2017
Helps clearly in understanding practical aspects of deep learning. An additional week, highlighting the aspects of productionizing a deep learning project would have helped
By Vinay N
•Jul 12, 2020
Since I myself am working on a few projects, the concepts here are somewhat useful in error reduction. Especially when the models are used to automate medical applications
By Palathingal F
•Sep 28, 2017
A unique course to understand the process of establishing a ML project. But lacks tools information and a more structured definition of the process. A bit too theoretical.
By Mahnaz A K
•Jul 2, 2019
Thanks for the practical tips and insights from real projects.
Your pool of heroes of deep learning is very skewed. If the field is so skewed, then it's a bigger problem.
By Vivek V A
•Feb 13, 2019
Good course for the ones who already started developing ML systems. This will help us in improving the ML systems and identify what can be done for which kind of problems
By Ivan L
•Jun 25, 2019
Most of the material was quite useful, but some was, perhaps, too obvious. Also, some things were discussed too thoroughly, and, in my opinion, that was a waste of time.
By Алексей А
•Sep 14, 2017
Would be great to obtain more concrete information.
For example, instead of "requires much more training data" to obtain "requires ~1'000'000 samples instead of ~100'000"
By Rafal S
•Jul 22, 2019
Excellent content overall. However, reiterates some of the knowledge already presented in the two previous courses of the specialization. Lacks programming assignments.
By Amir R K P
•Dec 7, 2018
I wish there was more examples, visualization and depiction of work with referral to papers or experiment here. or perhaps a bit of project management, data management.
By Pete C
•Jun 24, 2018
Enjoyable, but felt a little less challenging and more hastily assembled. Regardless, the material is valuable and as always, a pleasure to be instructed by Andrew Ng.
By Lars R
•Aug 29, 2017
The course material is relevant and useful, however, I agree with other reviewers that these 2 weeks should rather be a 1-2 weeks addition to one of the other courses.
By Andrew R
•Apr 30, 2018
Quick course. Worth taking because gives some practical guidance on what avenues to pursue when finding a optimal model (which takes into account human time required)
By Poorya F
•Dec 10, 2017
The first week is too long with repetitive materials. The second week is very interesting. However, I wish the course was designed such that it required some coding.
By Hany T
•Aug 27, 2019
Great course, great professor .. the only issue is that I feel sleepy every time I watch the videos :), it's some how single tone. Also the audio could be improved.
By Kody L
•Feb 16, 2022
Not quite as practical and informative as the first two courses in this specialization, but overall still quite enjoyable and helpful. Excited for the next course.