Excelent Course, in control and leadership ML Projects from a technical perspective of evaluation

I think this is a very important cours with a potential to save a lot of time for AI developres.

This is the best course out of five courses since It does not focus on math or formulas in detail

Very instructive guidelines for structuring ML projets and Andreew Ng is excellent in teaching it

Very different from what is available on the internet and exactly what I was looking for! Cheers!

Excellent! Very through and detailed course presented in a very a insightful and interesting way.

Excelente curso para você entender como funciona questões práticas dos projetos de Deep Learning.

Very informative especially in planning strategies in the development of machine learning models.

There is no project in this course, but I've learned some strategy, which is really helpful, too.

This course really is wonderful in the sense that it gives a proper direction to the ML projects.

I really enjoyed this course... I learned how to make strategies while solving real-life problems

Great course that gives practical tips on making AI models. The simulator exercises are nice too!

The course gives a nice overview of the problems one could encounter when working on ML projects.

Really helpful course. Lots of information on how should you drive your machine learning project.

A guided coding exercise that actualy models the "simulator" scenarios would also be interesting.

Andrew Ng is hands down the best teacher in this space. Excellent lectures and a well run course.

Take this course to guide you in the process of tuning parameters and splitting data sets wisely!

Pretty good overview, some knowledge not only for deep learning but for all algorithm developers.

Something is repeated from previous part， And one vedio is black， Wish editor can crop or modifiy

I stand by the words of Andrew: you will not find much of this in the textbooks yet. Great stuff!

Will need to revisit these lectures time and again in future while working or real life projects.

Brief, yet full of practical details useful to optimise the ML approach at the onset of projects.

This is very good source to improve my ml algorithm performance and how to construct ml network .

I liked the insights into how to approach problems, not something I've seen elsewhere. Thank you!

It only takes you a short period of time to get a lot of professional experience, thanks, andrew!