Andrew Ng gives a good satisfactory explanation of the techniques covered in this course. He explains when to use the technique, how to use the technique and how one can implement it in Python and then goes on to give an intuition behind it. I think it should work well for newbies (worked for me).

I've really enjoyed this course. It gives you a great deal of knowledge and I recommend this to anyone who wants to get an intuition of how to optimise, regularise and perform hyper parameter tuning to make your model learn efficiently. The variety of topics and depth offered was good. Thank you.

This was an extremely informative course which provided an in-depth knowledge of how Hyper-parameters of Neural Network affect the results and methods of tuning those parameters from improving results. The Programming Assignment provides deeper insights of applying the taught methods effectively.

This course adds to the first with what you need to make models perform well and fast in practice. Each part of the learning process has possible tuning, tweaks, optimizations to improve performance. The material explains why each tweak works, at least at an intuition level. I have learned a lot.

My second AI course certificate from Andrew Ng after I left Taiwan AI Labs. Even though it took me more than 2 months to complete because of my kids' winter vacation and Chinese New Year break. I did learn a lot about how to tune and optimize a Deep Learning network. Keep going to the 3rd course.

Great Course. This course does explain some optimisation algorithm with quit a good detail. That is a good part of it. Many less courses explain those algorithms at a level of abstraction an undergraduate student needs. Also, it shows the usage of tensorflow, which is used by major practitioners.

I think it's a great course for those who want to learn about technics related in Neural Network and don't want to know the mathmatical underlying too much, or for those who want to get an intuition or a picture about Neural Network. Thanks Dr. Ng and Coursera a lot for giving me a great course.

Very good course. We learn the basics of Machine learning and Neural Networks in the earlier course. It works fine when we work with the examples given here, but in real world, our basic program does not work. The tuning process is more important for a successful model. Thanks to Prof Andrew Ng.

Andrew Ng has a great teaching style, the lectures are always easy to follow and to the point. Weekly quizzes and programming exercises are very well done and help to reinforce the topics a lot.

The programming exercises in week 1 and 2 are very low-level and thus not relevant for real projects.

I felt like this course picked up specific problems and I was guided through them very well. Including theoretical aspects into the program assignments helped me to understand the concepts as I applied them! I also liked the funny comments every now and then. Great highly recommendable course!

This is a beautiful course that builds on the first one, it gives all the intuitions about various hyperparameters and makes us implement all that in python. Then he when we start working with tensorflow, it all makes sense because we actually know what is going on in the functions that we use.

Incredible course. Very comprehensive, and goes over some awesome, industry-relevant optimization algorithms. Clear examples, programming assignments are extremely helpful, etc. Only things to improve would be to increase the difficulty of programming assignments, and focus more on Tensorflow.

The content, examples, assignments, and quizzes are thoroughly developed. All the courses of the specialization share the same notation and lead a student from basic concepts to complex ones helping to develop an intuition on each step. The best course on topic of Deep Learning one could find.

It has tremendously increased my intuition about hyperparameters. It made me fully grasp all the concepts. I would like to write more code in programming assignments, but if you follow the code that is already written carefully, it will be intuitive enough. Many thanks to Andrew and his team.

I really enjoyed this course. I think it is really well structured. The videos of Professor Andrew Ng are awesome and helpful (being able to explain very difficult issues in a nutshell with several examples and straightforward words!). I'm excited to go on with the rest of the specialization!

The course teaches many SOTA techniques for tuning hyperparameters, various regularization techniques, various optimization algorithms. Howerver, it would have been great to get a hands-on on hyperparameters tuning in real. Rest, the course is amazing and paves a smooth way to deep learning!!

I am really glad to learn the tuning and optimization techniques. Hopefully, I can implement them whenever I need. Learning a new framework (TensorFlow) and using it to ease up the bigger calculations was the best thing about the course. Hats off to Andrew NG for designing a course like that.

This second course was great in terms of showing improvements. I would have enjoyed a little more rigorous treatment of why improvements work, but then the course could go on and on... I sill think Andrew can spend a little more time on overcoming overfitting. All in all, excellent balance!

It's a great course like the others and quite valuable. I am not quite sure how tensorflow fits into optimization, but I was glad to get a good, handholding kind of introduction to tensorflow as in these courses, I had become accustomed to doing things directly using numpy or MATLAB/Octave.

This course helps practitioner or beginner to know how to tune supporting parameters in order to achieve more efficient/accurate NN. In other words, this course helps me figuring how to optimize the NN design, and I think this is recommended for beginners who like to explore Deep Learning/NN

This course provided a lot of insight in how to improve accuracy by tuning hyper parameters and also introduced multi-class problems and Deep learning programming frameworks! Awesome specialization to have as it aims to create well rounded expertise in Deep Learning and Neural networks area.

After the first course, This course was really important for optimizing the Deep Nets and increasing its accuracy to further heights. The discussion forum also helped in clarification of many intriguing doubts. The assignments were suffice in implementing and understanding the fundamentals.

Отличное продолжение первого курса от этой организации. Множество важных моментов отлично описаны, а задачи по программированию помогают закрепить это на практике. Как отдельный курс наверное не стоит наверное смотреть, но если рассматривать всю специализацию целиком - это отличный продукт!

Coursera is so amazing to provide an opportunity like this to someone who is living in a 3rd world country with almost no opportunities in a high entry barrier field like Data Science. It is inspiring to see what coursers stands for, providing a learning opportunity to everyone, everywhere.

Nice breadth and depth of relevant topics in this course. Andrew Ng is as always very precise about the issues presented and helps build up our knowledge step-by-step in a super structured way. Nice to work with both Python (semi-raw) models and getting a similar introduction to TensorFlow.