The course will make all concepts about improving deep neural network understand in excellent manner by Andrew Ng.Must complete the course on deeplearning.ai.Mathematical concepts along with applciaitons are clearly explained.

This course is an absolute necessary for anyone who wants an in-depth knowledge of optimising their deep learning solutions. Loved the course work and I could easily relate the course contents with the practical aspects of AI.

This course provides a detailed description on parameter tuning and also deep mathematical aspects behind it. This is a must-take course to understand how neural network parameters operate inside and the way to optimize them.

This course helps me a lot to learn about tuning hyper parameters of deep learning, efficient optimize for gradient descent. Personelly, I love the idea of momentum for gradient descent.

Thanks for giving intro to TensorFlow.

Excellent follow up to the first course. Lectures and lessons are well matched to reinforce the material. A few minor errors in the programming assignments that have been pointed out in the forums that need to be corrected.

Really great course by Andrew. I am marking all of them as 5 stars. But these are not fake reviews. These are really great. As I have mentioned in other comments. I really like the style of Andrew of writing while explaining.

Learnt a lot about the different of the Hyper-Parameters & the different kinds of Optimization algorithms. Was really beautifully explained & made intuitive to understand. Loved to have an introduction to Tensor-Flow as well.

A little less technical than the first machine learning course for the Deep Learning Specialization, but very valuable nonetheless, don't hesitate to try! It truly is a good course and Professor Andrew Ng is a great teacher!

The content is generally great and well worth it. Perhaps the only frustrating aspect is navigating to the Jupyter notebooks. I wish the links to the notebooks were on the same pages as the Submission and Discussion links.

Again Andrew Ng did a fantastic job explaining complex problems in a simple terms which make the course fun to follow. The quiz and the practice exams also help better understand the problem and the concept behind the video.

Very helpful course that sheds light on the inherent parameters of popular 'black box' DL libraries. After passing the course you will be able to understand and variate the majority of those small but important coefficients.

Very helpful! This course helps me step into the details of deep neural networks in practice, and teaches me how to fix those issues, as well as Tensorflow which is a popular deep learning programming framework using Python.

Great course, sometimes you might get lost but its understandable due to the complexity of the topics, but doing the programming assignments helped me to solve my questions

Thanks to the mentors, discussion forums and Andrew

this course was much easier for me to follow, i am really grasping the core coding. really enjoy this course and the others from deeplearning.ai

but the notebook crashed again... but luckily only one line of code was lost.

It was a really good course, like the first one. The only problem is that we got the idea of hyper parameters. We haven't still figured out how to automatically set values of all hyper parameters. That was a bit sad for me.

Thanks a lot, Andrew. Now I know Batch Norm and Adam very well. With the TensorFlow assignment, I can say I have enough basic knowledge to gain more. The practice assignment was very well organized to gain TensorFlow basics

I'm not sure if those technics are still applicable with high-level libraries, but I really like the way Prof. Ng explains it and it helps me to better understand how it works behind the scenes of already written functions

a very good course to get started with hands-on deep learning. This will not only cover the hyperparameters and optimization techniques but also covers the underlying math and reasoning behind using it. It's fun! Go for it!

I'm always satisfied with deeplearnig.ai's courses.

All the lectures are making me understand very well with simple and easy explanations.

I really like to recommend this course to anyone who wants to begin the deep learning.

Good extension of the first course, covered with necessary (from a novice point of view) details.

Despite complexity of the subject, there was enough explanations, examples and hints to finish coding exercises in the course.

This course provides me with information that gave me a breakthrough in my machine learning programs. I believe using the algorithms introduced in this course will change an amateur learning program into a professional one.

Very good course. Andrew is very good at explaining these concepts. Before this course, I have spent entire weeks reading papers without understanding a single thing.

I really like the approach of the quizzes and exercises.

This course helped me acquire the essential knowledge behind the optimizers we use in deep learning. I always consider it necessary to know what is running behind those huge libraries in python. This course taught me that.

The course is easy to understand, and the assignment design is very thoughtful. Many parts that do not matter much with key knowledge have already been completed for us, which significantly improves our learning efficiency

It was a very helpful course because it unravels the mathematics behind the optimization algorithms and the hyperparameters. Also, the intuition about those algorithms was very helpful. Looking forward to the next courses.