Great and detailed strategies especially for people working on a machine learning projects. With good strategies, time and money may be saved. A really good complimentary material to Andrew's new digital book: Machine Learning Yearning.

Highly recommended as it helps one think how to improve their ML models. Just do a 60/40 split and hoping for the best result is not the way to go, and this course definitely helps unveiling how to remove bias and variance from a model.

this course has very practical and helpful advices to solve problems related to the deep learning algorithms. I believe those valuable advices and tips will be able to reduce tremendous times and efforts when you stuck with the problem.

One of the best tips to use in real ML consulting projects; Prof Andrew Ng is an awesome teacher

and keeps you engaged , by giving relevant industry use cases for each topic being taught; This

brings objectivity and motivation to learn.

Best course so far in specialization as technical stuff you can google and get tons of books and blogs for . But for real world insight into how to solve problems is a great thing to know and not easy to find out from other resources .

If it were possible I would give 6 stars! The most valuable deep learning course I'v ever seen. There many more technical courses but related knowledge can be found in books/on lectures. Knowledge learn from this course is exceptional.

Actually, the information in this course were very valuable since they could be only gained after long time of real practical experience. Transfer learning, multitask learning and error analysis topics are priceless. Great course IMO.

I think it will be more helpful for those who have actually worked on real ML project,for me, it's still kinda abstract and a little boring except for the week 2 ,so it's worthwhile to learn it again once I get some experience in ML.

Course is time-consuming because it with high concentration with information. Would be maximum useful for those who have some experience in machine learning.

I am very excited! Quizzes are so interesting and close to real life project.

This course was not what I had thought it would be. It helps to bring back the human dimension into the side of coding. Shines light on the importance of the process, and how decisions will impact the ultimate success of the project.

An exceptional course to hone your skills, and develop efficient Machine Learning and Deep Learning systems to better address the problems faced in the real world. The added experiences of Andrew are an asset to the learning journey!

Really useful quiz questions. I liked this class a lot even though there were no programming exercises. Getting some insights into the facial recognition and image classification stuff before course 4 was also really nice. Thanks! :)

Good course with a lot of qualitative information that is quite useful. Giving it a 4 because it would have been great if there were accompanying Jupyter notebooks. It's a solid course overall and I recommend it to anyone interested.

This course is highly intuitive, practical and less mathematically complicated. Prof Andrew Ng uses many examples to elucidate concepts. Post learning one will be capable of choosing which direction to go in solving an ML/DL problem.

This was a great lecture from Andrew Ng. I have learned basics of error analysis, multi-task learning and structuring a machine learning project in general. This will be very useful staff for my professional career. Thank you Andrew!

I consider this course is a truly gem because of the bunch of good practices every person getting into the field should be aware of. I also liked how quizzes were designed to address industry use cases and not just academic details.

Excellent point of view. many teach you how to do /write code to apply ML to your problem. in this course I felt they were teaching me how to understand the results and how to improve it. Extremely interesting for potential Managers

This course is exceptional since we can learn a lot with Andrew Yang's great experience with Machine Learning Projects. It'd also like to suggest to add new classes about powerful and newer techniques, such as feature visualization.

These are most toughest things, in which people takes 100 of hours to explain and still people confuse. But by doing this course within a 4 hrs span you will have a decent knowledge. Kudos!! to entire team and thanks a lot AndrewNG

This course covers lots of practical advice and techniques resulting from real world project experience by the author. I highly recommend this course to anyone involved in deep learning projects, even if not in a technical position

this course very important other than previous courses because we need to understand the data and split the data set across the train, dev and test and making strategies for training the dataset using model. Thanks for this course.

Great course with some awesome insights into structuring the analysis of machine learning models. Definitely picked up a ton of strategies, tips, and tricks that I will be using as a I move forward with my machine learning career!

The mindful advice does not only deepen your understanding in deep learning, but also stimulate creative thinking in my own PhD research in a total different field. It is also enjoyable to watch the interviews, which I favor a lot.

very helpful!

Andrew teaches a lot of knowledge that can't find in books.

This kind of knowledge is very helpful for student when he gets his hands on real-world ML project.

Error Analysis & Bias& Variance are all useful techniques!

Very helpful! The experiences of building deep learning systems might be very difficult to obtain through other classes. When learning from practice, however, the costs are too high. Thus this is a really marvelous course to take.