Many thanks for Mr. Ng and team for putting together this course and setting up the necessary logistics. It gives a good introduction for implementing a neural-network. Using cloud-GPU makes experimenting and prototyping less time consuming. Looking forward to next course in this specialization.

Regards,

Uday

Prof. Ng has again created a great course on machine learning for the public.

This 4-week course seems to be less mathematically rigorous than the 11-week Machine Learning course, but it's understandable--the goal is to get to deep learning topics sooner rather than later, and some material needs to be cut.

This lesson taught us the basic concepts of Neural Networks and Deep Learning. Then it emphasized on practice by teaching us how to build our own logistic regression model, shallow neural networks and deep neural networks, which could be applied to classify images. It is quite a useful and wonderful lesson.

Thank you! I am amazed. Straightforward notebooks, spectacular demonstrations, almost zero issues with the framework - that must have been a pretty lot of work. May I use the notebooks as a base for my classes in the DL extracurricular activity at PPKE ITK? These are far the best demos I have seen before :)

Thanks for letting me have the opportunity to learn and experience this amazing subject. This course had a very good and complete coverage of subjects and if I had a question, there was a great community where i could view other peoples ideas and answers to my questions.

thanks for having me in this course.

Im totally new to this field so i thought that i might encounter some problems to grasp the course materials, but it was utterly the opposit, in fact the quality of the course and of the instructor made it quite easy for me to grasp the fundamentals of neural networks and deep learning. Thank you coursera.

A very good course, it helps to deeply understand the mechanics of the neural network.

Separately, it is worth noting the excellent instructor Andrew Ng, who explains so complex and incomprehensible at first glance things. I recommend to walkthrough this course!

Thank you, Andrew!

Best regards, Pavel Bandiuk.

The teaching is very thorough and easily described. The materials are very descriptive. The quizzes are great to verify the learning. The programming assignments are wonderful because they develop the concept step by step. Last but not least, the lecture delivery of sir Andrew Ng is so engaging. Thank you.

Andrew Ng is one of the world's leading practitioners of Deep Learning and Artificial Intelligence, and he's also an excellent instructor when it comes to explaining concepts in a simple, lucid manner. This course is a perfect intro to Deep Learning that will set you up for a career in this exciting field.

This class is really a delight. The material is well structured and clear. The assignments are very well done, you can focus on the actual algorithms. The time estimates for the assignments were pretty accurate for me. If you took the Machine Learning class from Andrew Ng before, some material can overlap.

Extremely hands-on, easy going, easy to understand, progressive, attention to details. Most effective way of human learning of machine learning. Jupiter is also great; course materials are meticulously prepared, and are runnable and downloadable. Everything you wish, it is there. Thanks for the great work!

To me, there are still some mysterious parts of Neural Networks and Deep Learning after I completed this course. However, neural network and deep learning is not a black box to me anymore. I understand how it works now and I know if I have the data and formulas ready, I am able to train my own NN machine:)

It is a great course to start for learning Neural Networks and Deep Learning. Andrew clearly illustrates the concepts and math behind the algorithm. The homeworks are critical milestones in comprehending how to build a network and I suggest anyone with interest in Machine Learning to tackle this challenge.

The very carefully thought-out notation really helped me get through this course in just over a week, without any previous experience. The optional videos that explained the underlying mathematics of neural network architecture will be an invaluable asset for creating my own designs from scratch. Awesome!!

Probably the best in-depth course of neural networks, with a very detailed explanation on semantics using pure mathematics. The assignments were well instructed, not having to deal much with the python-specifics. Looking forward to attend the rest of the specialization courses. Keep up the excellent work!

Very nice course on neural networks.In this course we will get to how to build a simple neural network to how to build a deep neural network from the basics.But one should have knowledge of basic operations on matrices,vectors and calculus(chain rule) to understand the learning process of neural networks.

Extremely useful to understand the very basics of NN architecture, including the flow of all mathematical computations like forward and back propagation. Programming assignments involve implementation of NNs from scratch without using tensorflow or keras, thereby promoting better conceptual understanding.

This is so far the most interesting and involving course I had ever come across. Till before I started this course, I had been searching for a good course with both theory and hands-on practicals. I am really happy for starting this learning path for having found out where my research interest is aligned!

Wonderful program, a lot detailed explanation of how Neural Networks work. Mathematical concepts were explained so neat that it was easily grasped, the course material is designed in a simple manner for easier understanding. Overall loved this course, looking forward to complete rest of the specialisation

A very beginner-friendly course and the learning schedule can be agile. I've been using TensorFlow for some time but have a relatively vague understanding of the mechanism behind the interface I use, and the programming assignments in this course are helpful for me to gain the intuitions of deep networks.

Andrew is very thoughtful. The course is both suitable for beginners and old hand. We can always learn something from this class. It feels good that there is a master who can show you the big picture of deep-learning on a high standing and guide you through the beginning, which is always the hardest part.

I find this course very good and easy to understand. Inasmuch the depth that the instructor goes into , the course is very well structured and very easy to understand. Also, the programming exercises are very helpful and congruous to what is being taught. My sincere thanks to Andrew ng and coursera.org!!

There are a lot of courses, books and other resources to learn but only this one provides enough and theoretical and practical information. The math explanation is simple enough to be understood by anyone. The assignments are divided into intuitive small steps which allows to implement complicated models.

the best thing about this course is the programming assignments. They not only helps in understanding the concepts covered in the lecture, but also provides confidence to implement things from the scratch in your own working environment. Further, the interviews with Hinton, Arbeel, Goodfellow are awesome.

This course shows the "bricks" of the neural networks and gives a good intuition of how they work. I also liked that you have to make a few neural networks from scratch, rather than use a framework or something like that. This course is a great start in the field. Looking forward to complete the next one!