Introduction to Deep Learning

This course is an advance course which requires some background in machine learning or deep learning.

Comprehensive intro of deep learning The RNN week was very bad.

I think Coursera should sign up with GPU cloud vendors for deep learning courses.

This program is more suitable to those who already have mid level knowledge about the nuts and bots of Deep Learning and looking for hands-on opportunities to advanced skills.

This course provided a great introduction to deep learning with TensorFlow and Keras.

The lecturers did an excellent job explaining concepts and techniques and the programming assignments were perfect for getting started with implementing deep learning models.

An really good introduction to Deep Learning.

A good course for introducing the various concepts of Deep Learning.

This is a very hands on Deep Learning class.

This is the best course that I have taken so far about deep learning on Coursera.

Very practical course, provides all the necessary means for the deep learning dive.

Being trained as a statistician, I used to believe I'm a bit too oldschool to do deep learning, and now look at me using keras and Tensorflow!

The final project is a bit of a let down as it basically requires the user to do some data processing in python but no "real" machine learning.

I have painfully lost hours trying to understand how to do a reshape of a placeholder with not known sizes, but you are supposed to finish the exercises in 1h, while this is barely impossible if you do not know Tensorflow in advance.It looks like that you need to know both machine learning topics and Tensorflow, which means that you don't really need this course then.So I'm not sure what is this course about as it is not really teaching anything, topics are just presented and then you need to do your own research.

The course is more advanced than Machine Learning and DeepLearning.AI.

I really love the machine learning courses from National Research University Higher School of Economics.

Especially the most criticized program assignment part, some is not well detailed and guided (even broken), but it is also partly realistic to mimic actual machine learning project development.

I would recommend everyone to take this course but after having some "basic knowledge" of Machine Learning, Deep Learning, CNN, RNN and programming in python.

Thanks Strongly recommended for those interested in current state of machine learning algorithms i think that the explanations and examples in the notebooks was not always sufficient Great course.

Nice course to learn some advance level Machine Learning stuffs.

This course is very hands-on and would be a great addition to any one interested in Machine learning.

Definitely, this course is not for those people who are at a very initial stage or with no knowledge of learning Machine Learning.

This is a very nice course, it's part of the advanced machine learning specialization so it would make sense if the lecturers go fast through some mathematical intricacies.

Taking Andrew's machine learning class helps you enter the world, this series would take you to another level The video content is quite good and I've learned a lot.

There were a couple of issues with programming assignments, but I'm still giving the course solid 5.

The content of the course and programming assignments is well designed.

And some requirements for the accuracy/loss in the programming assignments are really too high.

The programming assignments are harder but are rewarding in asserting the skillset.

Lots of programming assignments which really helps improve our programming skills.

The programming assignments are intuitive with fill in the blanks kind of approach.

I liked that the programming assignments didn't have a lot of hand-holding and I ended up learning a decent amount of numpy/tensorflow/keras on my own.

Some programming assignments were not instructed enough, so it's very hard to solve them without discussion forums.

The provided 'example' codes - that work after successful completion - serve as a good starting point to build your own neural networks.

It contains nice explanations about different types of neural networks.

It's a good course for people with some prior experience and background in machine learning (specially neural networks).

Folks are trying to explain multiple architectures of Neural Networks, without giving an actual understanding why it works.

In general you will learn the basic about Neural Networks, Convolutional Neural Networks, and Natural Language Processing.

excellent In general the course is good, it gives you the idea of different neural networks, their usage and a bit of their inner math.

not very deep, but well-performed introduction to deep neural networks very difficult at times Good, however in programming assignments could be beneficial to add mathematical equations for computations or maybe add variables input.

Highly informative, and strikes a good balance of the application of neural networks and theoretical background.

This course does that and I doubt you will find a better introduction to neural networks in that respect.

Also, sometimes the language is not spoken perfectly which makes it a bit hard to understand.

You either need to understand Deep Learning, in which case the explanations are very bad; or you already know Deep Learning a bit; in which case the course doesn't bring anything.Generally, the instructors are hard to understand, it goes from 0 to 100 in a second.They also speak with a strong accent which doesn't help the understanding.If you want to complete the Specialization, maybe follow it and accept to lose your time and money.Otherwise, skip this and focus on better courses It's a very hands on course.

One has to struggle really hard to understand what they are talking about -- they often use concepts and terms that have never been defined before, the slides are sloppy and often formulas make no sense.

Fast does not mean good One of the best courses of deep learning !!

As for me, at present, the course is one of the best courses in this specialization.

one of the best courses I have attended.

I learn more when try to pass Numpy NN, GAN, LSTM and etc in spite of material, English (I realise that it is very difficult task to fit a lot of material in 5/10/15 minutes.

Amazing Great lectures and homeworks.They were challenging The explanation of TensorFlow is not enough and the programming homeworks have already a lot of already written (because, i would be very difficult to programming the all of the homework by ourselves in this stage of learning).

The course was awesome, I have learned lots of new things, clear some doubts, I have enjoyed a lot.

Even though I've done Andrew Ng's ML course twice and completed his Deep Learning Specialization, I learned a lot of new things in this Intro Course of AML specialization.