Good high-level course on how to think about projects implementing Deep Learning

A bit short and light to be a course on its own but still useful in the series.

Quiz answers were not that clear. They seem more "gotcha" than "deep learning".

It would be good to have more practical/industry scenarios added to the course.

Always great, but some little issues in the content makes it feel less perfect.

Great class overall. Some practice example on multi-task would have been nice.

Greate knowledge, but I had a hard time motivating myself through this theroy

Good background theory for people starting in the field to get familiar with.

Good learning , teaches us how to diagnose and plan machone learning project.

I would have loved more programming assignments and opportunity to practice.

I see the point, but takes too long to make it. But part of a great series.

useful hints and techniques to manage ML Projects and choose right approach

I thought the course was clear and gave useful tips in leading a ML project

A bit short, maybe combine this into other courses? Or expand it with labs?

Very useful tricks / method to approach typical machine learning projects.

I loved the use cases it gave a practical uses of what I've been learning.

Some hands on exercise to complement the theory would have been excellent.

I am pretty surprise that this course does not have programming assginment

provide student with some code tests like previous courses may be better .

quite detailed and easily accepted way of understanding all the materials.

Good and useful material. However the homework is not challenging enough.

Some video issues, give this course a slightly lower production values...

Very useful for people working in ML. Short on content but one of a kind.

Lot of blanks and glitches in the videos. Should be better reviewed by QA

It could have been the last course in the specialization instead of 3rd.