Wish it was a little more in depth about things that it taught. It was a very high level overview. Considering that it's a beginner, may be that is how it should have been. But I personally would have liked to learn things in-depth. Kudos to having us do lots of practical assignments!

The course content was really good. But as greed for more never ends, it would be great if we could be able to shed some more light on few gray areas like in what situations we should go for 64 filters or 32 filters, how to determine size of the hidden layer in terms of neurons etc.

Thanks to Laurence and Andrew for the sharing there knowledge which have all the foundation requires to get the AI understanding using Tensorflow , keras. Simply awosome .

This is really a refresher for those who already are into datascience field, even for the aspiring students too.

A truly enlightning and helpful course! I walked into this course with minimum machine learning knowledge and barely any deep learning prospects. Now finishing it, I am happy to attest that I am satisfied with the progress that I have made and excited to go on for the next courses.

It is a good introduction to tensorflow, The course is very easy you can finish it in a couple of days. The videos are short, so you have more practical content. overall I suggest the course for everyone having a background in Machine Learning and want to extend their Knowledge.

I really enjoyed the course and my instructors were all amazing! The videos, the Jupyter Notebook lab environment, the notes, they were all awesome. Going into this course as a newbie i was frightened but with the help of Coursera, i am transforming into a programming wizard.

This is a good introductory course for using Tensorflow. If you have finished the deep learning specialization, you will easily breeze through this course. It is an overall great course however, I feel that the instructor could have discussed the concepts a little bit deeper.

This course is great, it starts with beginning and slowly moves upwards but there is a lot of room for improvement such as the reading time in the weeks is total unnecessary and it accounts for almost 4-5 hours, and quizzes are way too easy and so were the weekly exercises.

Can be hard to figure out what needs to be done in the exercises (excepet week4). Also it would be great to have more resources available to understand the underlying maths behind some of the algorithms. Other than that, good intro to the TF library (mainly keras for NNs)

decent course to begin with, but doesn't take you into the details of all the parameters, functions used. Instead focuses more on solving the problem easily through Tensorflow. Could be better if given the rationale behind using all functions, choice of parameters etc.

This is fantastic stuff, made simple if you have done earlier course of Deep Learning from Dr. Ng this is at another level, I feel little confident that I may be able to code without copy pasting.. hopefully the next course in the series gets introduced serious stuff..

Good course which gives the brief explination on how to use the TensorFlow framework to solve many computer vision problems. This course is designed to such that the beginner too will feel more confident understanding the details of the machine learning techniques.

Overall, pretty good, clear information. The submissions were a bit annoying because of bugs with the system, but that wasn't anything to do with the course content.

Some of the "graded" exercises could have been a bit more thought-provoking and less "copy & paste".

This course actually gives you hands-on coding deep neural networks starting from very basic ANN to image classifier. The explanation is easy to understand and is more focused over practical part which is very important. Overall the course is an excellent starter.

Hello ,

This was very helpful , I gained some new information.

I can not believe that I finally used the famous tensorflow library , and this is my first time to do picture classification.

This course leaved me with some questions that I will try to research.

Thanks for the course! This course pretty much starts from where I left off i.e. Machine learning course from Andrew NG. And, I am happy using TensorFlow which saves a lot of time to experiment and concentrate on the problem at stake than the program itself!

I like courses that are longer and more in depth such as the first specialization of deeplearning.ai, I just could not continue that one because financial help always got me financed the first course which I had completed and cannot pay for the other ones

Nice introduction. Tests are too easy. Exercices are easy too, but still is fine, rather I prefer them to be more challenging (like: 'try to play with number of epochs and other parameter to achieve 99% accuracy for example ' and do not guide to much).

This course was a little too basic and introductory, personally. But the course structure really makes up for it. It is better suited for someone who is new into this field. Since I had half a year's experience in PyTorch, this course felt too simple.

Very good introduction with a lot of resources to better explain out-of-scope topics. I do wish the assignments and quizzes were given an update to be up to date with the lectures but luckily there aren't any major problems that googling can't solve.

The way of explaining the topics was very good. The number of assignments and quizes were sufficient enough to get understanding on the topics and hands on practise. The course was very helpgul for me to understand the usage of Tensorflow in DL.

I loved the fact that it was more hands-on than theoretical. Although I did expect some more explanations on some parts.. but the suggested links were good enough for those parts.. Overall, I loved it. Lawrence is really good at what he's doing.

Should have provided more explanation about the assignments. The explanation videos about the topics are no longer than 4 minutes. You should know some of the DNN concepts, then you can understands the assignments in depth and more clearly.

Not being able to run the notebooks on Coursera was frustrating. Fortunately, running them on colab wasn't difficult - just an unnecessary impediment.

Was nice to see some of the more abstract deep learning terms be put to use fairly easily.

May be provide resources to learn some senior grammar knowledge for python, because basic knowledge for python does guarantee we could understand the code perfectly, but simply remember its form in case of a particular complex line of code.