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Nunpy basics should have been covered in detail as calculus was covered in deep neural networks since is being heavily used in this course .1 Hour coverage would be excellent !!

Amazing course! Loved the "tour" of the different approaches in computer vision applications, and getting to see firsthand how they all work through the programming assignments.

wow, interesting topics! starting from building blocks of 2D convolution then branch off to many CV problems. thanks Andrew Ng, deeplearning.ai, 糖心vlog官网观看 for this awesome course

This course is mandatory for those who wants to learn machine learning and especially who wants to build an awesome applications that use image processing based on big data set.

Despite of some troubles in some assignments, I realize this is a great course. It gives a broad vision on deep learning convolutional NN applications in a good level of detail.

Content of the course and assignments are pretty good. Found some problem in submitting last week's assignments(read on discussion forum that coursera is working to resolve it).

This is a great course. Andrew Ng is a gifted lecturer. The course was well presented and the materials are easy to follow. I expect a similar lecture on reinforcement learning.

I appreciate this great opportunity to learn from you while I couldn't get to study at Stanford as an international from a developing country, this is a dream come true for me!

wonderful course with well organized course content and assignments designed in a elegent manner, I learned a lot form this course as well as from deep learning specialization

This course explains different CNN architectures, object detection, face recognition, neural style transfer in a very effective way; Great course to understand concepts of CNN

In his usual style, Andrew takes us into the world of Computer Vision. The main topics in the field are covered sufficiently which enables us to move on to more recent avenues.

I really like the case studies with famous models as examples, that swiftly brings me to a very good overview what each different tasks can covnet contribute to. Great course!

Before enrolling, i read the reviews that programs have many bugs. But as on June,2020 i didn't find any bugs. Everything is working fine. Good course to learn about Convnets.

This Course will give you a brief to intermediate understanding about convolution network. You will then have to practice on different data sets to have a firm grip on ConvNet

It's very useful, in this course, it show us not only the details of theory, but also many popular example of neural networks and algorithms! very good course, worth to learn.

Not only learned the concepts behind CNNs but also understood current important applications using CNNs. Thank you for explaining such complex topics in a fun and easy manner.

Ver interesting. Great course. I've been learning Deep Learning for some time, this course had the best explanations that I have found. And Andrew Ng its just a great teacher.

This is the most exiting course that i have taken in this specialization. I came know how to build many CNN models. Autonomous car driving most exited me in the whole course.

Very interesting. More challenging and complex than previous courses in the same specialization. This course clarifies how CNNs could be really helpful in real world context.

Great Course. Goes in-depth about convolutional networks. And try to explain the state of the art model archetypes as well. (at even Dec 2019 these models are worth studying)

As with previous courses, I really appreciated the teaching of Andrew: interesting, well explained, enjoyable, easy to understand even for a non natif English speaker as I am

Excellent material and presentations!

The assignments are more challenging this time, so don't expect passing them too easily.

Looking forward to the next course in the series!

This has been the best course in the deep learning specialization so far. There is a lot of content to digest, but it's broken down expertly by the lectures and assignments.