A unique course that dives deep into the actual problems faced during a machine learning project. My favourite part was the real-world case studies in the quizzes.

An excellent course you learn the principles of how to handle a machine learning project and which addresses to point to in case different types of problems happen

A very nice course which provides overview of carrying out machine learning projects. It provides a lot of insight into the non-coding aspects of Machine learning.

Great class covering the practical elements of ML not often taught elsewhere. This might be one of the more valuable classes in the 5-class deep learning sequence.

very effective and practical training, demonstrates methodologies I can use right away and how to be more efficient than an entire team alone! who can ask for more

I would like to think you for well organized ML deep learning courses. The contents were extremely informative and incredibly useful for my real world development.

It is great course and I learned a lot. both quiz are awesome and create another level of learning for me, so many thanks from Andrew and Coursera production team

Excellent course which discusses the engineering/project structure considerations of any project involving deep learning. Solid and practical advise from Andrew!

Great overview for the structure of ML projects. Every hour you spend within this course will save you a lot of time in real projects. This course is a must take.

Selflessly, the instructor shares his experience from many deep learning and machine learning projects. I learned some knowledge which I cannot learn from school.

Excelente curso, reune todo lo necesario para entender los problemas de las redes neuronales y como redirigir el enfoque, según el problema y la solución deseada.

Great and a unique course. Much of theoretical material in the other courses is available on the internet, but its difficult to find such things in organized way.

I gives better approach to deal with project. And performs better. More specially thanks for having test like that. It give best experience while performing test.

This course looks easy but this is one of the courses which challenges your subtle understanding of organizing ML projects. I really enjoyed the quiz assignments.

This is an amazing course full of insights from professionals. Which gives you a great insight into how professionals should interact in data science development.

앤드류 응 교수님의 오랜 연구경험에서 나오는 기계학습 노하우를 배울 수 있는 강좌입니다. 여러 번의 시행착오와 고민을 통해서 익힐 수 있는 내용을 짧은 강의로 가르쳐 주시니 시간 절약이 많이 됩니다. 다른 강좌에서 잘 알려주지 않는 팁이 많으니 실험 경험이 부족한 수강생들께 강력 추천합니다

Invaluable course covering the considerations that any data scientist or machine learning engineer should take when undertaking serious machine learning projects.

The Course is informative. Though many times I had the feeling that the course should have been Course 1 instead of 3rd as it gives you an intro to ML strategies.

Important insights on error analysis. Getting to know Transfer Learning, Multi-Task Learning and End-to-End concepts will be very useful when working on projects.

Full of fantastic practical advice that I haven't found anywhere else about machine learning in the real world, when you're rarely given the ideal amount of data.

You can learn really important guidelines for machine learning projects. And you can even test them with "real" projects at the end of each week.

Recommended 100%

Too fantastic! I really really enjoyed this course's quiz! So interesting quizzes are they. It makes me remember concepts easier and longer under real scenarios.

Really helpful in providing a systematic way of analyzing the performance of deep learning models and how to address real-world problems that you might encounter

I learned a lot about practical aspects of implementing deep learning models. This is a course i would like to revisit before I start any deep learning projects.

This course helps me to learn a lot of things to consider while developing a Machine Learning based system which are very necessary. That was a great experience.