Me parece un curso muy didáctico e interesante para aprender acerca del Deep Learning, aunque hay un largo recorrido aún por hacer para llegar a cimentar las bases del IA.

One of the best ways to start deep learning. I learned what's behind the neural network and this helped me a lot rather than directly using Keras or Tensor Flow libraries.

After going through this course, I am able make neural network modles for ML applications. Its a best course for beginners and covers all basic concepts of neural network.

It's an awesome course for intuituions awout neural networks. I think everyone should try it after getting some basic understanding about ML and DL from some other source.

Good balance between theory and practice. More detail regarding the format of the data set, how to get data into the right format and loaded into the model will be helpful

Very interesting course. I liked how everything was explained and how much detail everything was explained. Now I understand more about the possibilities of Deep Learning.

This is the best course, which not only teaches us the theoretical knowledge but how to implement deep learning! I feel so grateful to take this course! Thank you so much!

The clarity and the simplicity of the instructions in this course makes it a winner. Andrew can take some very complex problems and explain it in a very simplistic manner.

Die vielen Notifications aufgrund von Fehlern in dem folgenden Video haben gestört. Sonst war es ein guter Kurs. 5 Sterne, da das Wissen trotzdem sehr gut aufbereitet ist.

It's a great course to get started in deep learning which gives all the basic intuitive and mathematical foundation required for learning higher level learning algorithms.

The Deep Learning course by Andrew Ng sir was great , it gave me a very good intuition of building a L-layered Deep neural network from scratch and the way backprop works.

Excellent demonstration of Neural Networks from the ground up. Breaking down the problem into smaller functions eases the understanding. All concepts are conveyed clearly!

very good pace, not too deep, not too shallow, it is left to the student to dig further(math) if they are interested, main ideas and structures are well explained. Thanks!

Really excellently explained. Takes students by the hand and guides through fairly complex stuff, providing some good intuition along the way. I can only highly recommend.

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 .