Really a very good course to learn neural networks and deep learning. It is really a successful one because it teaches you how to start from the scratch. After this course, even if you use 3rd party porducts for deep learning you can be aware of what is being done in the background with the knowledge you get from this course.

Excellent course that sharpened my thinking on how Neural Networks work fundamentally. Always used to use neural networks as a black box for Supervised Learning tasks. After completing the course I feel more confident in taking up a difficult ML problem and write a deep NN from scratch to solve it. Great learning experience!!

Like always a great peak into the world of Deep Neural Networks by Andrew Ng. The lectures had as much math as it needed and they were not bombarding me with a lot of information but only with the really useful ones! The assignments were always leading me to solve the problems, maybe I would like them a little more difficult.

A good introduction to neural networks and some deep learning algorithms, It is just a nice kick start for the world of artificial intelligence, specifically deep learning. It will give you an overview, but bear in mind the road of learning is long and interestingly filled with application of deep learning to try on your own.

Excellent course that gets you coding right away and implementing the core algorithm in deep learning: Backpropagation. Ng is clear and concise throughout and gives plenty tips on how to code and avoid bugs. The programming notebooks are well constructing and easy for anyone looking to delve into the topic for the first time.

Everyone knows Andrew ng sir is awesome in teaching , This course is also excellent like previous Andrew ng sir courses, Doubt session is really helpful, TA's are responding really quickly compared to other platforms. I am very happy to do this course. Thank you Andrew ng sir, Thank you respected TA's, Thank you Coursera.

I loved the curriculum, it is in incremental approach.

But the clarification reading module is not in appropriate location, it is placed before the module and creating the confusion at the appropriate time, rather it can be the placed instance where clarification is needed, just like the optional quiz exam at the end of video

This course is too good if you really love mathematics. Astounding and Stupendous clarity in explaining topics.

Learnings:1. Mathematical model interpretation for Deep Neural Networks: Graphical, Linear Algebraic, etc.2. Programming ensuring Time and Space Complexity while Implementing it - Vectorization, Memoization, etc.

this is the best course I have been ever seen, who want to build their career in deep learning then this is perfect for it, but before u start this course u have good knowledge about machine learning, and for machine learning, u can start Mr. Andrew ng course then after u will enroll on this course this is my recommendation.

Extremely helpful review of the basics, rooted in mathematics, but not overly cumbersome. Very helpful for who want to understand deep learning from scratch. Very clear, and example coding exercises greatly improved my understanding of the importance of vectorization. The teaching techniques of professor Andrew NG is awesome

Even though I rate this course for five stars, I would like to express my concern about the vast amount of repetitions throughout the videos. Most of them could provide just the same information being about two times shorter. Apart from this, I am extremely grateful to Mr. Ng and his colleagues for sharing this great course.

Thank you so much Coursera for providing me such a good course. It was a great learning experience. The assignments and quizzes played an important role in improving my skills and giving me confidence to implement deep NNs. I'll definitely recommend this course to others. Looking forward to do more courses in deeplearning.ai

A very nice ,deep and comprehensive introduction to Neural Networks and Deep Learning.The instructors are fantastic and the complex Backpropagation has really been presented in a very simple,concise and easy to digest way and the way Andrew Sir teaches it no more looks to be a mathematically complex Deep Learning algorithm.

The way Andrew covers all the concepts is, brilliant. It covers all the mathematical concepts behind an algorithm and explains them in great detail. The programming exercises give a good insight into the application. This course of the specialization is ideal for a beginner in this field . Can't wait to finish the next one .

This course perfectly explains the foundations of neural networks. You will understand the maths behind scary words like "backpropagation" in no time, and you will code everything by hand using python. This means that in latter courses when you use tensorflow, you will understand why you do what you do, which is wonderful :)

A simple and wonderful course. Goes through the basics of Neural Networks at the perfect pace. The assignments are well prepared and guide you through the implementations of your own NN models. For those who have an interest in Deep Learning and are familiar with Python, this course is perfect! Would definitely recommend it.

Best course if you want to break into deep learning! Concepts are explained well. Assignments have a lot of guidance, but are still challenging. Most other online courses are either too high-level (jumping straight into a heap of code) or too low-level (hardcore calculus derivations). Really enjoyed this one - very balanced!

I had some theoretical knowledge of neural networks and deep learning earlier. However, this course helped in understanding the basic concepts better. The vectorization part taught in lectures are specially helpful. Thanks to Andrew Sir and all the team involved in this course. Looking forward to CNN and RNN courses.

-Manish

I feel this course as an elixir for those who want to learn Deep Learning from scratch. One suggestion to provide if other platforms like MATLAB could have been provided for this who are expert in MATLAB or any such platforms. It would make the course especially the programming assignments for flexible and student-friendly.

I've heard about Andrew Ng before even taking this course that he's a great lecturer, having taken this course I found that there's a massive truth to what I heard. I really like the way he took me through the toughest and complicated concepts of DL. He was amazing!!!. I'm gonna take his future courses with the same delight

I was very new to programming but still managed to complete this course because Andrew is the coolest professor out there. The assignments help you understand the practical bits and assist you with your own ideas too! I'd completely recommend, even if you're an absolute beginner but have a little exposure to linear algebra.

Loved this course. Started following this one having a minimum experience is Machine Learning and Deep Learning, and now I feel like I have acquired a strong foundation knowledge in Deep Learning with all clear understanding of the mechanics behind it. Looking forward for the other courses of this specialization. Thank you.

This course explains theory and usage of NN and DL. I am engineer so I'm glad to learn them including fine techniques when implementation.When I was in trouble with not be graded on my code, I resolved by watching forum threaddiscussed same problem as mine.Thank Andrew, assistant , heros, classmates and see you next course!

This course explain the theory behind the neural networks in an intuitive way along with practical implementation of NN without using deep learning libraries (in the first course). This is very important to get to know the NN operations in each and every layers before dive deep into the other more complex NNs architectures.

This course is very thorough. Andrew Ng has made the difficult concepts most accessible. The video material and the coding exercises are closely interlinked and it reinforces the concepts. The coding exercises are very practical. The interviews with the leaders in deep learning at the end of each week was most informative.