Very important and valuable intuitions about DNN training/optimization. It's full of really practical information while implementing my own models.

DNN을 실제 적용할때 반드시 이해하고 적용해야 할 실질적 내용들로 구성된 멋진 코스 입니다!

It is a special lesson that guide me to think how to build a good model for ML. There is no doubt that Andrew ng taught his project experience without exception and hope that we can benefit from it.

Excellent course to understand the various nuances of structuring these kinds of "projects". Though if the content were presented as parts of programming assignments could have been easier to grasp.

Andrew Ng, awesome teaching technique and well-designed course content make it easier for deep learning beginner to learn how to structure your machine project smoothly and do not lost in a process.

The course was very insightful on how to tweak and evaluate and measure the performance of your model. I loved the course very very much. Hope to see more courses from deeplearning.ai and Andrew.

This course gave some very useful tips on how to start with a Machine learning project when I was struggling to do so. It also gave useful information about error analysis and data set distribution.

I think this is the most useful course in the Specialization. Andrew reveals secrets about details which can speed up working in Deep Learning. It will help to avoid marking time in future projects!

Generally, the course is great. This is a short course and could be combined with other courses in this series. Also, some knowledge such as data splitting has been introduced in the courses before.

The course gives a sound intuition and insight into the parameters to be considered and the crucial thought process involved in making the decisions for improving the performance of neural networks.

Really a good course with mostly the theoretical knowledge on some aspects to reuse your model as well as some error analysis. Thoroughly taught with lots of real-life examples, thanks to Andrew Ng.

It's a great course! This course gave me a lot of new perspectives in constructing a machine learning project. Especially, the discussion of data distribution in the train/dev/test set is fantastic.

Insights distilled from long experience, explained with simple examples. Probably like explaining quantum mechanics to someone who didn't arrive at the conclusion through rigorous first principles!

I really liked this course, such as I liked the rest of the courses in this Specialization. I honestly appreciate that this knowledge is shared, accessible, and made extremelly intuitive and clear.

Really a good course and got an insight into how to structure a machine learning project and some useful techniques for deep learning, such as transfer learning, multi-task, and end-to-end learning

Interesting course especially for ML novices. A short course and could be completed quickly, however, one needs to carefully review the lectures to avoid missing key points. Well-structured course!

Although this course is the shortest one from the specialization this course have really valuable insight about how to propose a systematic way to solve a problem with Machine Learning techniques.

While there are lots of techniques out there, this course really helps you gain a different perspective on the bigger picture and teaches you to avoid some of the common pitfalls you may encounter

Fantastic! As is pointed out by Andrew Ng, the material is not taught in other courses. You will get answers for a lot of things you might have wondered when working on a machine learning project.

Shorter than other courses in this specialization, but realy important. It helps to structure machine learning projects to shorten the time and effort and to prioritize the different alternatives.

Very insightful thoughts from an expert and legend in Deep Learning and ML. Well explained and easy to digest the information. Keep up the excellent work Andrew and thank you for your hard work!

This course taught so much about strategy and intuition on how we structuring our machine learning projects in order to save time and gain expected best results and what to do in our ML projects.

Impressive course to guide us in planning machine learning projects. There isn't any calculation or programming exercises but we can gain the intuition that will take years to develop, I believe.

Wonderful course! Great learning content and I love the quiz at the end. The flight simulator model for the quiz is fantastic. The bonus interviews were very interesting and exciting. Thank you!

Fascinating insights how to solve issues in ML projects. Saves lot of time if you have to find out yourself. Great share of experience and very appealing and practical examples, easily explained.

This was very insightful.

No rocket science, but taking to heart these lessons may save you and your team months of work.

Pragmatic way of thinking about getting your deep learning project to work.