Structuring Machine Learning Projects

This course would be immensely helpful for those who have not started on their first machine learning project. However, the insights shared are quite commonsensical and intuitive for those who have already had some minimal experience in machine learning. This course also does not feel as substantial as the other courses in the specialization, though the tips provided are definitely valuable.

I recommend this course. This will be a bit of theoretical which is good. It will talk about real world scenarios over the errors which is what we deal in day-to-day life and how to deal with it.

more practice!

Though it might not seem imminently useful, the course notes I've referred back to the most come from this class. This course is could be summarized as a machine learning master giving useful advice.

I learned so many things in this module. I learned that how to do error analysys and different kind of the learning techniques. Thanks Professor Andrew Ng to provide such a valuable and updated stuff.

A lot of concrete examples, including those in the lectures and in the tests. Gained some thoughts on how to manage a ML project. Thanks Andrew and deeplearning.ai for providing such a great course.

This is a must course in the entire specialization. It covers the step by step procedure to approach and solve a problem. The case studies provided are real world problems which are so much helpful.

This is the knowledge in which we will get from lots of experience only, but the andrew has shared in this course which might help us in future by saving a lot of time through this course experience

Going beyond the technical details, this part of the course goes into the high level view on how to direct your efforts in a ML project. Really enjoyable and useful. Thanks for making this available!

I'm glad I spent some time on the "Flight simulator" assignments in this course. It's the first time in the specialization when I actually found the quiz questions challenging, and that's a welcome change. However, I didn't learn too much from the lectures. They were too repetitive, either repeating themselves or the material from the previous course. One or two videos could also do with better editing work: I could hear Andrew making a soundcheck, and there's a 30sec segment that's played twice in a row. Overall, it's probably worth doing this course, given that it requires very little time, and the assignments are useful.

Time wasting, all could be summarized in 30 mins video at the end of the previous courseThis specialization has increased my knowledge and passion to learn about machine learning.but that course took me alot as i really hated wasting my time watching aaaaalllll these videos for nothing really really small amount of useful informationSorry if i was rude, but that's my opinion and that's because i really appreciate coursera contribution in knowledge sharing especially for those who can't afford it (like me)

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.