Great explanation of fundamentals with some good exercises. Side-effects include refreshers on linear algebra and tools like numpy. I like the clarity of this course, for example, the separation of the linear from non-linear parts of a neural network layer and why that matters.

Needed a grounding in deep learning and this course helped me with that. Well streamlined with all the necessary data/code to perform the coding exercises and have them graded fast. My comfort level to be able to apply this to solving real business needs have improved greatly!!

I really liked some of the intuitions provided by the instructor, especially the intuition behind the several layers in NN in context of images, and audios.There are quite a few typos and errors, and they need to be corrected, especially the ones in the programming assignments.

The course is really good. But the videos are grouped to one complete module followed by complete implementation which becomes a zone out. After each lesson is complete we can also take up each implementation(cells in the notebook). This could be good for better understanding

I have taken other courses about neural networks and they were using a built-in module to implement neural networks but in this course, we build a neural network from scratch and now I have deep and better understand what actually happen inside the black box of neural network.

Amazing course, I found the mathematics behind neural networks very interesting. I also wanna give major appreciation to the use of notation and symbols in the course, it was perfect and not unnecessarily complicated, unlike other courses and textbooks I've seen on the market!

Very good course, teaches the fundamentals of deep neural networks very well and particularly the importance of vectorization is also stressed well in this course. The programming assignments give us a good feel on how to implement deep learning by giving interesting examples.

This Course provided me with an excellent base to venture into the world of Deep Learning. It helped me grasp critical concepts which would enable me to start working with Deep Learning on my own. Now i can safely move forward with the remaining courses in this specialization.

This course explains the basics under Deep Learning, it is not as other courses that goes directly into applications using it as a black box. It is part of a specialization on which you will also learn how to go to applications, but with the knowledge about what you are doing.

Helps you clearly understand the fundamentals of neural network and deep learning, Andrew NG is amazing at explaining complex topic in an easy to understand language and he also tells you tips and tricks to work more efficiently. Great starter course to get into deep learning.

Amazing course! I took machine learning course first (which is also amazing!) and then started this one. They are both good for beginners, some of their content overlaps, this one can be well stand-alone - don't worry about it if you have not taken the machine learning course.

Great introduction into Neural Networks and Deep Learning. Andrew does a good job with explaining the concepts and the simple programming assignments reinforce the learning. You won't come out a wizard in NN/DL, but it's a great start to continue to motivate future learning.

Excellent Course, the mathematical details provided in the course helps in understanding the working of Algorithms to the fullest. Although, it would be very helpful if some detailed textual content can be made available for each chapter to take the understanding even further.

It is a Comprehensive course on Deep learning and undoubtedly the best in courser, providing every detail on how to work and make your model, still I would recommend to follow Stanford Machine Learning Andrew Ng course once to lay a rock solid concept before starting off here.

I have learned a lot from Andrew Ng in this course and the teaching and exercises' style is consistent with that of the Machine Learning taught by Andrew Ng. Generally speaking, the python programming style is very pretty and I will follow this style to program in the future.

I have been in touch with machine learning and computer vision since my MsC degree on a ivy-league faculty.

I think this is a very nice and smooth way to learn, even after a 9-to-19h full-time work day. So, thank you very much for making this course so well prepared, so smooth.

Thank you Andrew Ng, you are my best teacher who I have seen. The programmer exercise part are designed so wonderful and I have a deep understanding to Neural Networks and Deep Learning with it. I am going to finish the rest courses and finally I want to say, "I love Coursera"

Professor Andrew makes the difficult subject easy to grasp. Simultaneous implementation of the techniques taught allows for better clarity of concepts. Also, the segment where heroes of Deep Learning share their journey and ideas is inspirational. A very well designed course.

Thoroughly enjoyed taking this course! Professor Ng is one of the best teachers I have encountered. The videos lectures are an easy watch. Assignments are designed to really solidify the concepts. A little bit of calculus knowledge will definitely help but not really required.

This course has been a such a good fundamental learning experience. Andrew Ng's way of instructing was very intellectual and easy to follow. All of my learnings in this course makes me feel confident in my journey of becoming an AI engineer. 10/10 would recommend to others 💯

This course is exceptionally well-designed, making a seemingly challenging subject easy to understand. Andrew Ng's detailed explanations and the step-by-step guidance in the coding assignments make deep learning accessible even to individuals without a strong math background.

Excellent introductory course with Python as programming language. If you are beginner at ML and looking for headstart this course is for you. Andrew Ng leaves no stones unturned un explaining the basics, plus he makes things lot more intuitive without involving much Maths:)

Very nice Deep Learning introduction course by Prof Ng. He explains concept like forward propagation, activation function, derivatives and matrices in a layman way and actually motivate me to do more further reading on matrix calculus and various forms of activation function.

The best course to follow up after ML from Deeplearning.ai. Dive-in deep to understand how back-propagation, hidden -layers and the activation functions are developed and used. Design and develop multi-layered Neural networks with greater understanding. Thoroughly enjoyed it.

I have to say this is the Best Course u can get if you want to Enter the World of Deep learning

with to the point Explanation of the relevant topics and the hands on Exercise Bridges the gap between the Theoretical and Practical approach of this domain. cheers to Knowledge.