Enjoyed the class and would recommend to those who wants to know more about the hyperparameters relating deep learning. Materials well explained by Prof Ng and assignment equally well designed. Looking forward to the next section.

Liked the content of this course. I would have liked optional videos about the mathematics behind the optimization algorithms. Appreciate the focus on building the optimization algorithms from ground up before learning a framework.

A great course. I appreciate the way how Andrew Ng explained all the technical details which i have never able to understand. Before taking this course, it used to be black box for me. Many many thanks to the great teacher of AI.

Andrew Ng explains everything so well. I am still a high school student without any calculus background yet, and I can still understand all the concepts. I recommend this course to any young individuals getting into deep learning!

Nice course on hyperparameter tuning, regularization, and optimization. Those who are research scholars will get deep knowledge. Working professionals get good hints for improving the model and accuracy through various techniques.

I enjoyed the every bit of this course! It is very well structured as always and optimization methods are clearly explained. I like the last programming assigment the most. It gives you a solid grasp of Deep Learning architecture.

Andrew NG is masterful at explaining complex things in the clearest possible way teaching all and only you need to get an understanding of the subject that is good and complete relative to the goals of the course. Amazing teacher.

Very well explained and detailed. The less positive aspect is that I think the programming assignements are a bit too easy. But for the rest it's perfect, it's always interesting and clear. Thank you for the high quality content !

Prof. Andrew did justice to the topic. The course contents are very insightful with respect to how the choice of parameters initialization and optimization techniques could influence the overall outcome of a Neural Network model.

Nuts & Bolts of deep learning were very well explained thought in this course which will be very useful in building a robust neural networks. Maths behind the concepts were explained clearly. Thank you very much Prof.Andrew Ng !

An amazing course that talk about hyper parameter tuning, regularization and optimization of Aritificial Neural Networks. Andew's practical advice about these subjects are really helpful, when we perform these tasks on our own.

This course really helps me understand different optimization functions, regularization and dropout these valuable tools in depth. Implementing Adam and Momentum more or less from scratch makes me feel more familiar with them ;)

Great next step to the First Course. The jump into Tensor Flow was a little sudden and maybe we could've had some more smaller exercises mimicking other problems in Tensorflow before the new one came up for the final assignment.

The main advantage of this course is the amazing capacity of professor Andrew Ng to facilitate the understanding of key concepts on Deep Neural Networks. The assignments help a lot to improve the comprehension of the concepts.

I am so grateful that Andrew and his team provide such great course, after completed the course now I have more understanding about different optimizer and regularization methods of the NN. And practical exercise with tensorflow

This course is awesome. In the end of this I can understand the how to make your model more efficient and optimal. How I can play with our training set and how to improve the our Deep Neural Network.

Thank you so much Andrew sir.

I like the way Prof. Andrew explains intuitions and how Momentum works in Deep Learning. Also, this course gives practical explanations of how improve models. I would recommend to anyone who want to start learning Deep Learning!

All the techniques taught were very effective. Before this course, I made a NN without knowing these techniques and it was a pain to get it to converge. Hopefully, after applying these techniques. it is performing very well now.

This course is excellent to get a start of deeplearning.

I really emphasize this.

Dr. Ng is an awesome professor who can simplify abstract and complex concepts to a really linear knowledge flow i.e. removed activation layer hahha

This course was very valuable and informative, and I wanna say a special thanks to Dr. Andrew NG, a great professor. Thank you very much, and finally thanks to the Coursera for giving me the opportunity of learning this course.

This course gives me a comprehensible insight into the tuning of hyperparameters in the Deep Learning. It gives me a better understanding by some useful and practical exercises. I really want to say thanks your efforts, Andrew.

I wish there are exercises for coding back-propagation on Batch-normalization and multinomial logistic regression from scratch (using python and NumPy only). That would help to deepen my understanding of those concepts greatly.

Good stuff. All in all well worth the few weeks to get a better idea of how to thing and deal with parameters.

I feel like I need a real course on tensorflow though. Documentation and tutorials are not googles strong point.

Very rich with information on various ways Neural Network training can benefit from optimizations. I'm sure there are many more optimizations to explore, and this serves as a great introduction to some of the more common ones.

The optimization algorithms and the the introduction to tensorflow were the topics I liked the most. Although hyperparameter tuning is important, this seems to me to be still very empirical. Also, more interviews would be nice.