The course is great, Andrew Ng. has a very impressive way to explain the abstract concept that may require a serious understanding of related matters. Thank you for making a good course.

Very good. Very nice and easy to understand the brief explanation and hands on with Tensorflow. Now it all makes sense. The mathematical background given in course 1 is indeed essential.

Really well structured course that builds on the techniques learned in the previous class and teaches lots of new information quickly and effectively. I feel like I'm learning so much!!

Good content to help understand how different techniques can increase, or decrease, the success of your models. Really shows how little tweaks in certain hyper params can go a long way.

Excellent introduction to practical aspects of applying deep learning. Demystifies so many of the core concepts and you gain valuable intuitions about many useful and practical methods.

This Course is well organized and geared toward beginners. I enjoys the content in each week's lectures. Hopefully I will explore more documentations to improve my skills in TensorFlow.

Excellent practical material Teaches good intuition on how to train a model. Has answered many questions I've had. There is currently no other single source that addresses these topics.

A solid introduction to hyperparameter tuning and setting up the optimization problem was given by the instructor. I was expecting a more brief introduction to the Tensorflow framework.

This is a really good course after the intro course!! Even if you do not have phyton or AI experience like me, this course helps you through it and gets you to understand the principles

The most exceptional course I have ever seen. Really I never thought that deep Learning will become so simplified with this.

Hats off to the mentors and a special thanks to Andrew Ng sir

i really liked this course,most concepts are nicely explained.

I just think that the part abourt the tensorflow framework should be more developped.

Thank you for this excellent material.

It is a good course. I have learnt a lot from all of the sessions and now I am getting more and more confident in building neural network by myself. BTW, I am ready to take next course.

Dr Ng explained the fundamental things so clearly. In order to be a good developer on machine learning, you need to understand what is going on underneath the framework you are using.

Initially I thought this course to be a simpler course but eventually it turn out be a very conceptual and applied course. So this leads to a lot of learning. In fact Extreme learning!

This course is very useful for the computation of hyperparameters and Neural networks. This is helpful for the intermediate practitioner. I suggest for the go through this course once.

The teacher's explanations are in place and easy to understand. Arranged assignments are also very helpful in mastering the content of the classroom. In short, it's a very good course.

Recommended course for understanding the importance of hyperparameters in Neural Networks and understanding the structure of the optimizers used for training (gradient descent to ADAM)

Wonderfully designed course, I understood RMS Prop and Adam so well that I felt why other articles are so complex. Your explanation on exponentially weighted average is simply awesome.

Great at building foundations in deep learning, I have already worked with Tensorflow some, but now feel I have a better understanding of what the commands are doing behind the scenes.

Great course. I learned a lot, and the exercises although seems a little simple at times, really improves confidence in trying to implement and teaches some good conventions to follow.

For the everyday practitioner of deep learning this course is definitely a must. Professor Ng explains the most important empirical techniques in the day to day use of Neural Networks.

Just like the first course of this series, it is really a very good course. Everything was explained clearly. Not doubt. the highlight of this course is teaching style of Professor Ng.

It's great to know how machine learning algorithms work, but I'm glad I can now also use them with TensorFlow. The practical assignments were very interesting, especially the last one.

Great course that covers the optimization algorithms and advanced hyperparameter tuning concepts in greater depth. The last week also introduces the deep learning frameworks in details

Its a very informative, in-depth course and nicely ties in with the previous course in this specialization. It demystifies the cloud of tuning parameters briefly discussed in Course1.