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.
Mar 31, 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.
автор: Bryan H•
May 29, 2018
The course appears to be in development and could be strengthened with programming assignments that take you through an actual mock project. Otherwise, the current content is enjoyable.
автор: Tri W G•
Mar 10, 2018
Not so much different with the materials in the Machine Learning course from Prof. Andrew Ng itself. If you don't have the time to finish the ML course, then you should take this one.
Jun 28, 2018
A good approach to ML strategy. However, having a programming assignment to better explore results from tweaking models based on the strategies discussed in the course would be great.
автор: Richard J B•
Nov 20, 2017
Developing intuition on how to structure projects in deep learning is essential to becoming effective and productive. This course is a good start for gaining that experience quickly.
автор: Iver B•
Oct 22, 2018
Valuable information that is well-organized and clearly delivered. Would benefit from a larger number of shorter exercises each week to cement learning after each group of lectures.
автор: Danielli I•
Mar 30, 2020
This is a great course with excellent contents and guidelines !
Point for improvement:
Please add a programming assignment in python and the questions appearing during the lecture....
автор: vivek v•
Jun 23, 2019
This course provided an empirical approach in tackling hurdles in solving most common issues faced by data scientist in solving Machine learning problem in a very simplified manner.
автор: David A N•
Mar 18, 2020
I really appreciate learning about the high level strategies for designing machine learning projects. I only wish there were some programming exercises to put it into practice.
автор: Søren B•
Jan 29, 2018
Based on my own experience and comments on the discussion forums, I get the impression that the quizzes have a couple of errors in them that makes it impossible to achieve 100%.
автор: Juan Z•
Nov 09, 2019
This course is less pratical and theoretical. I don't mean it is not helpful to me. I think this course might be helpful as guideline when I hand on the real project in future
автор: annestay e•
Nov 04, 2019
very good course, but I felt like it was lacking one more week of course to get deeper knowledge about how to really get data sets and how to set them up for real applications.
автор: Christian V•
Jul 18, 2019
you may think because the course is shorter will be much easier but the videos has a lot of information to process. I am excited to tried this techniques on real applications!
автор: Ambrose S O O•
May 25, 2019
A good course. Provided general high level thinking and reasoning for quick problem solving, data management, multi-tasking, transfer learning, and error reduction techniques.
автор: Sayantan A•
May 23, 2018
Not as exciting as the previous courses, but informative nonetheless. A section for handling imbalanced or skewed datasets would be useful, especially for multi-task learning.
автор: Aleksi S•
Feb 22, 2018
Not as deep into details as the two first courses in the specialisation, but nevertheless I learnt a lot of techniques that I hope will be feasible when I work on AI projects.
автор: Charles S•
Nov 29, 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.
автор: Akanksha D•
Jan 07, 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.
автор: Juan M•
Jan 04, 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
автор: 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.
автор: Uddhav D•
Jun 02, 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 :)
автор: 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.
автор: Carlos S C V•
Apr 16, 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
автор: 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
автор: 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.
автор: Mahnaz A K•
Jul 02, 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.