I really enjoyed taking this course. The use cases and practical strategies to the problems were really insightful. I'm really excited to apply what I learnt from this course on my own personal projects.

I learned a lot of new methods to structure not only deep learning projects but also ML projects. Very interesting and gives a wide overview of how we can improve our project management in AI in general.

Excellent course - Andrew's teaching is what's so needed in the machine learning community. He explains concepts properly so that one truly understands them, and thus knows what to do when applying them.

Prepare you for the problems faced in machine learning projects, I'm now capable of analyzing projects for other people although I'm only in the path of Machine learning for 40 days.

Thank you, Sir Andrew

I believe Andrew Ng shared some key insights into building successful machine learning projects. I really enjoyed the course and believe the shared information to be invalueable for my further research.

This is the most important course of all the machine learning courses from deeplearning.ai. I learned in two weeks, what normally will take years of experience from this course i.e. ML project strategy.

Well structured course for structuring machine learning projects. I've looking forward to go more with similar learnings. It is very helpful to expand an idea. Shortcuts with projects are promised here.

That course is so valuable in order to drive into a ML project. Especially, the project life-cycle simulator are really awesome to practice model diagnostic and what to do next !! Really amazing module!

A very unique and practical-based course that really shows the intricacies involved in making a machine-learning project and Andrew has really provided with hardcore lessons from his enormous experience

Course is really useful in explaining which part to focus on to reduce the error and how to detect which part of algorithm should be given more time to reduce error and improve performance of algorithm.

A bit more theoretical this time. But the information is worht the time. I think that the knowledge Andrew is spreading will make me more efficient in my AI jobs ahead. At least I hope and think that :)

Andrew Ng's excellent teaching style leaves you with an intuitive understanding of machine learning setups and potential pitfalls. For me it's the best way to learn; this stuff really sticks in my head!

Incredible course, so full of practical advice from Andrew Ng. Ah, and speaking about transfer learning, I cannot stop surprising myself of Andrew's ability to transfer his learning from him to others.

Very well structured course about all the little tuning things to be done to actually make a machine learning algorithm work well. It is really a course to be taking as part of an overall ML formation.

Really interesting!

We used to be concerned about unbalanced train/dev/test, and with this course I realised this are not the main problems for achieving performance in ML

A master class.

Thanks Andrew!

not as technical as the first 2 courses in this specialization (and the next 2 for that matter), but it is still a well rounded course and highly recommend to do all the courses in this specialization!

Extremely interesting and useful practical advice that can help make significant difference when thinking about how to identify and correct problems. The quizzes were fantastic and made me think a lot.

Excellent material. I would say this is the most important course of this specialization. Knowing how to approach a certain problem can indeed save us a lot of time and help us avoid a lot of mistakes.

This course gives great intuitions to develop deep learning model and how to go with deep learning project. I was really impressed and felt like I gain a real experiences without working at industries.

Excellent start for digging into topics that are not taught nowhere else. The author books 'Machine Learning Yearning' is a great next read that goes deeper in some of the aspects, really recommended.

It is good course that gives the practical insights about implementing the machine learning problem. However, it is better to have some coding exercises to be able to grasp the idea more efficiently.

Very helpful tips for navigating possible problems that would likely occur while building/training a model. The "pilot-training" exercieses, that mimick real-life problems / projects, are excellent !

Excellent. Just one remark: sometimes I do not understand quite well the english sens of the sentence. But in overall the course is well structured and I've learned quite a few things in ML Strategy.

Useful to know what are the steps that should be taken after obtaining results. Tho there isn't much information regarding making machine learning projects here (ie. there isn't any hands on project)

I am glad I took this class. There are a lot of things think about with respect to structuring your M/L project. Fortunately, it is not as mysterious as people often claim...but it is very nuanced.