Love Andrew's approach of keeping things simple. If you want to understand the basics of Deep Learning and get good INTUITIONS of how things work, this is it!! I had already experimented with Keras in my past but after taking this course I realize I should have done this earlier!! It is quite important to understand what the libraries are actually doing. That is when you get a good sense of what you are actually doing and most importantly, you ENJOY working on it!!

Fantastic introduction! Andrew really explains this well, in-depth and in such a friendly, encouraging manner. Regarding the programming exercises: there is a fine balance between guiding the student in the right direction with hints and the student encountering frustration if the answer cannot be arrived at within a given time-frame; I think these exercises were well-balanced in that respect. A thumbs up and 5 stars for this one -- I thoroughly enjoyed the course!

very good intro to deep neural networks; some topics are perhaps treated a bit too quickly and without much details on the underlying mathematics, but the core concepts are there and very well explained.

The coding exercises are a bit too simple, almost spoon-fed. On the other hand by completing them one gets a collection of working routines for NN that can be reused in other projects.

I only audited the course, so I cannot comment on the graded exercises and quizzes

I really liked the course. I already took the machine learning (ML) class by Andrew Ng and must say that I do like this one even more. The programming assignments are very helpful and using Jupyter Notebook is very convenient and much better compared to the textfiles in the ML class.

Would definetely recommend the course! But one has to be aware that it can be frustrating when one gets stuck here -->I highly recommend the Discussion Forums .

Thank you for the course!

This is a great course. Prof. Andrew Ng gave a lot of effort to design the course. Rather than diving into neural network directly, he build the intuition from logistic regression - that's really impressive. I am really amazed by his teaching methodology.

And the programming assignments are too awesome. In theory, he build the mathematical foundations which are implemented in the assignments. Learned a lot from this course.

Hats off to Prof. Andrew Ng and the team.

In this course, Andrew takes you through the essential skills needed to build a neural network architecture with only one output. This is the right way to start, and I liked the hints provided in the exercise notebooks to guide the thoughts of students not only to solve the exercises but to understand the content of the lectures. I will definitely recommend this course to anyone who wants to start learning deep learning and also building deep neural architectures.

This course was Awesome, and thanks to Mr.Andrew NG for teaching the course in much simpler and in an understandable way. It is really a pleasure to have taken and finish this course as it gave a good image on Deep Leaning and Neural Networks. Quizzes after each week's module was very entertaining, but, some programming exercises were quite difficult to get through, initially, but after getting more insight on the week's content and lectures, we could get it done.

I was very impressed by how well organized this course was. The information was well-chopped up and presented in bites that were easy to digest. (FYI: I know a LOT of calculus.) The lab assignments especially were well designed, where we only had to write the relevant lines of code to complement the main structure that was already created. This allows the student to focus only on the material learnt in the course and not all of the intricacies of Python, etc.

I think every ML enthusiast, must consider taking this class, a lot of good explanation that can be considered looking into for research topics. Hey ! anyone aiming to be ML-specialist needs to start from here, I bet you, you won't regret it. And for you, students out there, who are quite lost in ML class should consider this wonderful well structured and explain ML concept to the basic level. I rest my case. rat-ta-ta-ta (Million gunshot salute), to Andrew Ng.

A very easy to understand course for beginner and even people who familiar with machine learning. I used AI before, but want to go back to study more about the basic, and this course help me to reinforce my foundation in machine learning.

A lot of mathematics problem is explained in a way that easy to understand. Exercises are built to help you understand the concept. Lessons are much easier to understand than other online lecture (or even lecture at university)

Online learning needs lot of motivation, quality and engaging content, and right mix of difficulty level and comprehensiveness. Having attended grad school, I experienced that many of the MOOCs are really lowered down in terms of difficulty level and quality. I must admit that this course from Andrew Ng is one of the most engaging as well as comprehensive that I have taken. I eagerly look forward to completing other 4 courses in the deep learning specialization.

To the point course. Nice videos with an enthusiastic Andrew. Good progression, I and found the quiz'es good (somewhat easier than the ones in the Stanford 'Machine Learning' course. I would suggest some more backpropagation/chain rule emphasize early in the course (as in CS231n) as this is so fundamental for understanding the latter parts of the course. I enjoyed the 'Heroes of Deep Learning' videos, even though the topics discussed were to advanced, of course.

Just finished the course. I can't express in words how good this course is for starting deep learning. I'm feeling very confident now about the basics of neural network.Every beginner should start deep learning with this course. This is the best course I've ever seen for deep learning. At first the assignments felt really hard to me to solve. But after the 2nd week I felt very easy to go with the assignments. Hope I will be able to finish the other courses too.

I liked this course more than the original "ML" by Andrew NG. This one is more concise but still very practical, it's always super interesting to try and classify cat vs non-cat ;) It starts from simple linear regression, then adds one hidden layer, then generalizes to L layers. Every step is explained in detail (maybe sometimes too much detail), and is easy to follow.

Using Jupyter is super easy, much better than having to install and deal with Octave / Matlab.

This course explains the basic principles and maths behind Neural Networks in a way that is easy to follow and apply.

The weekly quiz and assignments emphasise the main points of the lectures, and enable you to apply those learnings in python code, without requiring you to spend days or weeks trying to put all the code together yourself.

If you're time-poor, but want to learn about Neural Networks and how to create them in python, then this is the course for you.

Brilliant material, no errors, relevant examples and exercises. Professor Ng is extremely experienced in the field of machine learning and AI, and each step learned throughout the course is directly related to a task a machine learning engineer would implement in the field. Glad to have taken this course, and I would recommend it as an introduction for whoever is willing to take the challenge to profoundly understand neural networks as a machine learning tool.

Great course of a great instructor to learn the fundamentals of Deep Learning. The programming exercises are perfect, because they don't require you to write a code of 50 lines without any feedback before you submit like in other Coursera courses. Instead, the exercise is split up into many small exercises and you program only the main part of all functions and can immediately verify your result. Looking forward to the remaining courses of this specialization!

Best course of Deep neural network I can find online! The lectures are straightforward and clear, from 1 layer (logistic regression), to 2 layers, to L layers, ..., every word counts! The quiz questions cover and emphasize the most important concepts of the lectures. The best part is the coding assignments provide enough details for students to understand the implementations of DNN with Python. After finishing this course, I understand the fundamentals of DNN.

Andrew NG is by far the best AI educator I have had the chance to learn from. His unique method for explaining complex ideas in an intuitive manner makes it a pleasant experience to learn from him. The course structure was very good and the programming assignment really helps to build a strong understanding of the concepts. I would highly recommend this course for anyone looking to learn deep learning. I will definitely be completing the entire specialization.

I had some experience on building AI system with ML framework but I never really understood what is happening behind the framework. And this course explained how actually the model, the network updates itself, how we actually train the model MANUALLY. It is really useful to know the fundamental, in order to build and optimize better system in my career. Also, instructor explained the maths, and complex things in a simple way which is great for people like me.

The course is awesome. Teaching Methodology is also awesome. Programming Practice exercise help me to use all the knowledge you gain from videos step by step and then cumulatively you apply those steps to make a complete model. One thing that should also be there is to provide the dataset and give homework to apply all those concepts that we learned in this course and practiced in the programming assignment from scratch. I wish this will also be added soon.

I've been willing to understand the concepts of deep learning and came to know about this course from none other than Andrew NG. Took the specialization and now I know what exactly is happening behind the scenes. This is not the first course I took from Andrew NG, and in every course I felt amazed as I got so much to learn and understand about the concepts of machine learning and deep learning.

Thank you so much for this course and the complete specialization.

This is a great beginning for someone who want to get into DL especially if you have completed the ML course by Andrew N G. He gives a lot of intuitions which is very important for taking decisions further on your projects. This is the selling point of this course that it not only teaches the concepts but also simplifies it in the form of intuitions and the assignments were pretty fun too. I almost finished course 2 as well and am very excited for CNN course.

Excellent course, as an intro to Deep Learning. It combines both theory, practice questions and interactive programming assignments. I totally recommend this course to anyone interested in adding ML to his bio. I also had some experience before to NN as part of my course and new allot theory from the artificial neural networks course from Brilliant, which is a great introduction to anyone that is interested in pursuing ML as a career choice!

Thank you Andrew

To put it in few words: Thank you so much Mr. Andrew Ng and your Team! You are enabling very high quality education for people who cannot attend classes e.g at Stanford. Never have I seen such a complex topic explained in such an easy to understand-and-digest manner as in your Course. You have helped so many others and me who wants to dive into artificial intelligence and enabled a whole community to build and research in the field of A.I. Humbly, Thank You!