The course materials scope, the instruction and homework are so excellent that you feel there is nearly no any obstacle for you to understand when you are leaning and practice when you just learn through homework

Great continuation to the first course. Builds nicely on the necessity for hyper-parameter tuning and optimization. This course will take me a long way into reading, and understanding modern deep learning papers.

Wonderful course. I am grateful for the detailed Tensorflow assignment at the end, since using such out-of-box libraries makes sense. But also the concepts underneath has been made very, very clear in the course.

It's the easiest course for various deep learning techniques I have seen so far while touch base on critical concepts. Programming assignments are not hard to follow even for someone with no technical background.

The topics covered in this course make the difference once we train our model. Thank you Andrew for this amazing course and your outstanding explanations!! I love the Hero interviews and the jupyter assignments!!

Great course! Andrew NG has a talent for explaining the details of applying Hyperparameter Tuning, Regularization, and Optimization. Thank you, Coursera and DeepLearning.AI for providing such fantastic material!

As usual, Andrew is best at teaching anything related to deep learning. The course is well organised and very informative. It also introduces you to TensorFlow which is an important framework in machine learning

An excellent course indeed. I will be proceeding to the next one in the specialization. As usual, a lot of math, but explained thoroughly and excellently with aplomb. The TensorFlow framework sure is convenient.

Excellent course, the complex notions are made easy. The programming assignments allows to apply the content of the lessons in an easy and very instructional way. Looking forward to complete the specialization.

Highly recommend the course. Andrew go deep on the detail and nuances of deep learning giving the math and the practical application laying a good foundation on the understanding and application of deep learning

- Very good explanation. I have learned a lot about hyperparameter tunning, batch norm. Beside that, this course also introduces about tensorflow framework, which make easier for me to create and fine-tune model

Great course that starts to delve deeper into neural networks. Also, there is a good introduction to using Tensorflow for neural networks that was quite useful.

Great presentations and good programming exercises.

I just love this series of courses. The best courses I have ever taken online, and I have taken online learning on most major platforms. Huge shout out to Andrew Ng for producing such excellent set of materials.

Excellent course. Andrew makes the concepts easy to follow and the programming assignments also help to get a more practical understanding. I am glad I now understand the big words that scared me some time ago.

This course really helped me to make my concepts crystal and clear. Previously, I read books and slides on this topic; now by doing this course it helped me grasp the topic well. Thanks a lot, Andrew Ng and Co.

This course is for you if you have the data and was looking for experimenting with the data using the neural networks. This course takes the nn to the next level, where several hyper-parameters were introduced.

Clearly critical if you're programming a Neural network. But also critical when using a software framework to build NN - since these have many parameters. This course explain what they are and how to tune them.

This is an amazing course! It will take more than 3 weeks if we are not familiar with the concepts already. But we really get to learn all the industry standard techniques in great detail. Throughly enjoyed it!

Again, some of the best material I've found online. I've never seen several things explained as clear as in this course. Including Momentum, RMSProp, Adam, hyperparameter search, hyperparameter distributions...

This courses enables me to speed up my Gradient Descent algorithm by several ways. Additionally, I have opportunity to approach programming framework Tensorflow, which is really concile for me in DeepLearning.

This course really helped me to get into mathematical intuition used in deep learning and motivates to learn computer application by understanding mathematics behind that instead of programming using framework

Great follow-up course by the instructor after the Neural Networks Course. Got an in-depth understanding of hyperparameter, regularization, and optimization. Kudos to the team for designing such a good course.

It i very good course! I would suggest to have multiple smaller programming assignments during the lectures specially when the material is explaining the math on regularization, optimization and normalization.

I found this course, as someone with a bit of experience in math and machine learning, more useful for me than the first course. But in all the cases I find the specialization super useful, and very well done.

Again really simplified way of teaching complex stuff.

Some additions for future coursework:

1.) There is some project at the end of course

2.) Also, if you could share arxiv links to relevant research going on