I think this is the best way of understanding the models we build and train. Now I can understand where are the errors are coming from and how to focus and choose an error rate problem to solve.

Great course with one caveat: some of the questions in the quizzes did not have clear-cut answers, where the correct answer could change based on subjective opinions rather than objective facts.

I made detail notes for courses in this specialization. The supplemental notes in this course helped so much for me to save time making notes. If I can give 6 stars, I will. Thank you very much.

This course is extremerly useful for being successful and efficient in a machine learning project. I'll highly recommend this course to take if you want to speed up your ML project and research.

This is a very unique course! Nowhere else is practical ML covered in so much detail. Many of the questions I struggled when doing ML are addressed in this course in a very clear manner. Thanks!

Please include more of programming. Until this course I have a decent idea of strategies for deep learning but still I am not sure if I can actually apply them that well to build a decent model.

Ce cours permet de donner un retour d'expérience sur des projets de Deep Learning réels, et nous confronte à la réalité des difficultés quotidiennes que les acteurs de ce domaine ont a résoudre.

It's great to learn the theory, and it's a great expansion to the earlier courses. It's slightly less fun not being able to do the coding course work. As ever phenomenal lectures from Andrew Ng.

Amazing course contents and case studies to get a solid understanding of key Deep learning concepts and applications in real world scenarios...very helpful for freshers in Deep Learning like me.

Very important course to master understanding of bias and variance, as well as overall error analysis. Quizes are challenging, but trying multiple times helps you better understand the subject.

Ótimo curso para aprender os princípios básicos de estrategias com o intuito de solucionar problemas quando trabalhos diretamente no processo de engenharia de modelos de aprendizado de máquina.

Learning how to better deploy and analyze Machine Learning issues has helped me a lot in understanding the issues and finding solutions for my thesis project, in machine vision for agriculture.

I like the "flight simulator". Excellent scenario-based training. I also like one of Ruslan's advice - code the backprop of CNN from scratch to really understand deep learning. Keep it up :)

This is the most down-to-early and hand-to-hand course of the whole series so far. For real world projects tuning, this course may save you months of efforts and tons of cost. Highly recommend!

Taught a lot of tools for tweaking the NN in a comprehensive ways. This course makes me want to jump right in and practice all those tools available (even without programming exercise provided)

Great course underlining that one should think first and then implement. It also helps to understand where to put the effort when we face real-world AI challenges. Thank you guys, great course!

This course was very helpful for me to understand more about building a good deep learning system myself and working with others to build one such system together. Thanks for the good lectures!

I learnt a lot. Keep the good work for the whole team behind the course. Personally to Prof. Andrew Ng, thank you for your easy way of explaining things and achieve what I have achieved so far.

This course give valuable insights on how to work more efficiently and explains very well some ways to improve decisions when one is part of a team solving a difficult machine learning problem.

Andrew is again great in breaking the course down into easy to understand concepts. I enjoy how he always makes a comment not too worry if we did not understand something from the first try :)

I hope my mentor will live for thousand years. The world needs person like you. I have learnt a lot. Confidence as an machine learning engineer is increasing day by day.Thanks a lot Professor.

Definitely should not overlook this course. It may seem small, but provides the insight needed for major projects. Consider this as precious gems of advice that you should follow like the law!

I have a feeling that other people/ books don't seem to discuss the material in this class that much. But the material in this class might be more important in practice than the other theory.

This give you guidelines how to approach a machine learning problem. You will get experiences from the tutors instead of struggling years to find out what should have done in the first place.

This course teaches a good amount of practical skills which can help approach a problem in a way that can save a lot time. I wasn't expecting something that useful and complete. Great course.