Jul 1, 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!).
Mar 30, 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.
By Devansh K•
Jul 17, 2020
Great course! Content was very interesting and did a good job building upon the previous courses. Enjoyed the assessment in the for of the simulator, gave me a good sense of real world Deep Learning applications.
By Pablo T•
Feb 13, 2018
Teaches how to debug a lot of design and implementation issues that happen when going from theory to practice. This is is the kind of knowledge that you can get from Prof. Ng's experience, but not in a text book.
By Sampath T•
Sep 27, 2021
I would like to thank coursera to giving me opportunity to follow Structuring Machine Learning Projects course. In the last few weeks I learned a lot of new theories and basics of improving deep neural networks.
By Bibek B•
Aug 31, 2020
In this section I learnt about the theoritical part of ML strategy, how to set goal, compare with human-level performance, Error analysis etc which I think will help me to develop as Machine Learning Specialist.
By Seungjin B•
Aug 23, 2018
This is a great course but I think it'd be even better to place it after Convolutional NN course. And also wish that there were coding assignments, too, as in other courses in this specialization (Deep leaning).
By Kate S•
Jul 1, 2018
This class will give you some practical tips on moving deep learning projects along. How to focus your attention on the most important things to improve. Some techniques for using other work to move yours along.
By Nektarios K•
Apr 28, 2018
Great course to understand how best to structure and evaluate the performance of your deep learning project. Invaluable information! I actually used info in this course on my real-world project to great success.
By Jose-Fernando E•
Oct 8, 2017
Very good course, focusing less on coding / tech aspects and more on the know-how and "art" of the seasoned practicioner. Very useful for acquiring both loose hints and structured approaches. Highly recommended.
Aug 26, 2017
Very useful and practical knowledge. Indeed, this will not be available in any books or theoretical literature. This is very valuable set of suggestions coming from years of experience and research by Andrew Ng.
By Timothy Q•
Jun 17, 2020
As Andrew said, you will not find a lot of content in this course in a very structured way throughout the internet or other courses out there. This is a must take if you are a Data Scientist or an aspiring one.
By Terence T•
Nov 1, 2020
Excellent course. I really enjoyed being confronted with real life deep learning problems and hoe to go about structuring the project. The "flight simulators" were really beneficial for my learning experience.
By Sean D•
Sep 9, 2020
Great course with insight into how to prepare your ML and DL projects and the order of operations and caveats and considerations to take into account with your data in real-world scenarios. Highly enjoyed it!
By Christopher M•
May 26, 2020
Excellent, very valuable to have advice on how to troubleshoot and make progress with a project. ML is not just about equations and code, and this distilled wisdom will help me get started as an ML researcher.
By James M•
Feb 7, 2018
This course offers great insights on building a ML project, which are also applicable in different types of projects in real world. Also, this is truly distinguish from other deep-learning courses on internet.
Jan 19, 2020
Learned about how we should manage our DL project and what to priotize first, these are something one learns after he has gone through such problem, so it was nice to learn about it beforehand from the expert
By Andrew B•
Aug 7, 2018
I thought this course was very helpful in analyzing neural networks. While I did enjoy the quizzes, I wish there were more to test my knowledge on whether it is more quizzes or actual programming assignments.
By Minh P•
Aug 16, 2017
Very practical, simple short course!
Very good materials that can generalise how to build a good ML model.
Very handful exercise
Nice interview from experts
This is a MUST TRY course, because it's too BEAUTIFUL!
By Username U•
Jul 29, 2021
This course was great! This course details various strategies behind creating a machine learning project, as well as the theory behind those strategies. This course is a great mix of practicality and theory!
By Upesh N•
May 19, 2021
The most informative course that i have ever encountered in this field. I am training deep learning algorithm for my thesis, after taking this course I am able to do a lot of things that improved my network.
By Sergio A D C A•
Apr 20, 2021
It was very useful for me to learn about posible sources of error when deploying a machine learning model, and how to fix them as well as improve it with artificial synthesis or transfer learning techniques.
By Marn Y T•
Oct 27, 2019
As a college graduate who took ML classes in college, this course is a lot more useful in terms of developing an intuition toward iterating on ML projects. The interview with Karpathy is the cherry on top :)
By Yash B•
May 2, 2020
This was truly amazing! I mean an entire course on the subtleties of gaining skills that we can actually apply in real life is really needed. I am super glad I took this course! Special Thanks to Andrew Ng!
By Marco A•
Oct 4, 2018
This is a quite different class. It's less math, less formulas but there is so much to learn from the experience of Professor Ng, a whole lot of best practices to follow and tricks to learn. Great contents!
By Dawid D•
Aug 9, 2018
Great and unique course! I think that such topics should be a part of any professional ML course.
Having said that, it would be appreciated if the sound volume had higher expected value and lower variance :)
Oct 22, 2017
This course gives me an overview sight of the whole process of machine learning project. Not only I know about the technical things, but also know how to structure and point out the position of the project.