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Truly truly amazing experience, I am now confident to take on any Machine Learning conference as I know the backbones of the algorithms implemented. Thank you Sir Andrew !

This course is a great introduction to deep learning mechanisms, and is really useful for starting to develop your own models. Do consider taking the whole specialization.

This course is very useful and makes one's understanding about Neural Networks a lot better. Would recommend everyone who aspires to get into NN to start with this course.

A very good interactive and hands-on way to get experience in building deep neural nets! Would like more derivation and/or techniques on the derivative of multi-layer NNs.

This was a really fun course! However, I feel that not enough emphasis was given on how the derivatives were obtained, which seems like an important part of deep learning.

Some of the exercises are boring, as all the information is in the text or, for example when computing matrices dimensions, they are shown bellow in the assert statements.

it provides very fundamental knowledges, from calculus to basic tools of linear algebra, enabling a beginner who prepare for entering the gate of neural network naturally.

Phenomenal course! Kudos to Andrew Ng for creating something that's even better than the ML course. Python programming is much more intuitive than Octave. Highly recommend

This is very easy to digest. It is hard to fail the practice tests at the end of the sections. I think I have gained a good understanding of how to build a NN on my own.

I found this course deeply interesting and helpful. It is well organized that all pieces of deep learning knowledge are sequentially and logically connected to each other.

Wonderfully designed course,i just want few concepts to be added if possible Andrew Sir:Gradient vanishing issue,

effect of number of hidden layer over gradient vanishing .

Great balance of depth and not getting into the weeds. Meticulously designed programming exercises. Thoughtful meditations on how to understand and approach Deep Learning.

It was quite challenging to understand the math behind. You will larn to program your own Deep Neural Network. ANdrew is a very good teacher. Highly recommend this course!

I enjoyed doing this course immensely. Prof Ng has a unique style of introducing a very complicated content in an easy way. The hands on coding exercise were very helpful.

I would like to thank the organizers of this course for all the effort in making a clear and rich material. I have learned way more than expected! Great job and thank you!

The course is really good. It makes your fundamental very strong. The programming exercises are well designed. We can learn how to design the API for our ML projects also.

This course worked wonders for me. It's the perfect place for someone looking for learning deep learning from scratch (nitty-gritties of neural networks and its working).

i love this course because it helps me understand the basics concept of neural network and it also reminds the knowledge i learnt in Machine Learning specializtion course

Thank You Andrew NG and the rest of the team for this amazing course. Even highly complex mathematical formulation was explained in a simple manner. Thank You so much...

Very well designed course. Right level of challenge and guidance in programming assignments (my favorite part!) Highly recommend for a practical intro to neural networks.

Es excelente! el datelle como se explica la teoria, la calidad de los pr谩cticos en incre铆ble. Recomiendo 100% hacer este curso porque da una base s贸lida en deep learning.

Really nice introduction to (deep) neural networks. I especially like that you get to try the concepts from the lectures directly in the homeworks. Very clearly laid out.

I really enjoyed the course and learned about fundamentals of the Neural networks with some practical implementations. I liked the way graded assignments were formulated.

It's really nice to have this material available online. I would appreciate additional optionial excercises and complex material to read (recommended papers, books, etc).

The course has been prepared exceptionally. With a minimal amount of prerequisite, anyone can learn one of the most complicated field of Mathematics and Computer Science.