I learned professor's machine learning course first, but in NN chapter there are some questions for me, so I take this again. Highly recommend this course, the material and professor's interpretations are more detailed and explicit, but I think as he mentioned in machine learning, python is not the best tool to do this work.

Keep learning!

Excelente curso, extremadamente didactico con un excelente material en todos los campos, a pesar de que entregan muchas herramientas para resolver las tareas, ya que casi hay que seguir los pasos, estos pasos estan implementados de una forma de aprender de la forma mas correcta las implementaciones que nos entrego el curso, muchas gracias.

I was knowing some of the concepts before attending the course. However, I could still learn many things like Vectorization, some Python commands (first-time experience with Python), logistic regression, etc. Moreover, the course helped me to give clarity on the subject via both the lectures and assignments. Thanks to Andrew and Coursera.

I really appreciate it that the process of building an NN and the maths behind it were clearly shown in the lectures and slides.

Since I finished the coding homework under the guidance of the notebooks, I think there is still a long way to go and many pratices need to be done before I can write codes and build an NN for a project by myself

I loved this course. The only drawback i found is that some of the things can be made more simpler which is just being made tough. i am just talking in the context of begginers but course is awsme i loved this course. i learnt alot from this course. Thanks andrew ng and thier team for making this knowledge sharing platform thanks everyone.

Very good. I already knew most of what was being taught, nevertheless, it still taught me how to organize the code and vectorize implementations. It also contained great insights on the inner workings of ANNs. The interview with the heros of machine learning was a very pleasant surprise too. Looking forward to making the remaining modules.

Well structured course and provides a good in-depth insight about Neural Nets. I would highly recommend to anyone interested and willing to get their hands on deep learning, start with this foundational course and you will not regret it.

Sending all love to Coursera team and special thanks to Andrew NG for making this course super awesome.

This course is amazing thanks to Professor Andrew Ng's talent in explaining extremely advanced math derivation in a beginner-friendly manner. I learned so much about the entire implementation of neural network, revised on linear algebra, calculus, writing modular codes and several software engineering techniques in scientific computation.

Excellent continuation to the Machine Learning course of Stanford University by Andrew Ng! The Machine Learning course touches all the Machine Learning techniques and gives a good introduction. It is taught in Octave/MATLAB. This specialization dwells deeper into those concepts in Python. Thank you deeplearning.ai!! Brilliant professor!!!

Andrew Ng takes you step by step in to the concepts and reinforces the basics along the way. The program assignments were also designed in a way that all the plumbing work is taken care to let the student focus on neural networks concepts. I would encourage anyone who would like to understand how neural networks works to take this course.

Andrew Ng has a gift for teaching, making things as clear as possible while still covering theory. Then, he helps keep things moving by eliminating some of the peripheral coding keeping you focused on the topic. The result is you learn some coding but have a firm foundation of how and why it is supposed to work, the best place to start.

If you really wanna know how deep neural networks work, you have to take this course. The programming assignments are so detailed and offer deep insights that literally deciphers deep neural networks at the highest level. The teacher and the TAs of this class did an excellent job throughout the videos, quizzes, and programming assignment.

"Neuronal Networks and Deep Learning" is an exceptional Course the explanations are excellent and so detailed that allows you to get a unique understanding of the crucial functions and components that make Deep Learning work.

Thanks to professor Andrew Ng and everyone that make this Course possible, it was a fantastic learning experience.

I just submitted the final assignment for this course and I must say that I am truly impressed. The videos were well made and the practice questions and in particular the assignments have the right level of guidance and challenge to guarantee a fulfilling learning experience. I am looking forward to the next course in this specialization.

This was my first course in Neural Networks and the instructor explains the lessons well, combining a little calculus with programming applications. I like how he emphasized and trained the audience with matrix dimensions (the dimensions of parameters), since this topic cannot go unnoticed in setting up even the most basic neural network.

This is a great introductory course in Neural Networks. The attention to detail in term of notation is very helpful. The videos with guests talking about how they got into AI and their experiences were wonderful. The programming exercises were well structured and organized. The building blocks approach to coding is rightly stressed upon.

I found this course a terrific entrance point into the world of deep learning! While the lectures gave a great theoretical foundation, the actual programming assignments provided me with a hands-on opportunity to build a multi-layered deep neural network to recognize cat photos. Which in itself is funny, but makes it also quite engaging!

Excellent coverage of the deep learning course, it had the right amount of complexity to ensure actually learning is achieved. The detailed discussion on the mathematical building blocks of neural net, plus the python implementation is excellent - all tied into the Programming Assignment was top notch. Looking forward to the next course.

This course gives awesome basic knowledge and entry into world of deeplearning! Though programming assignments are not challenging enough, it's always possible to try writing everything by yourself from scratch after completing them, so I don't really agree with negative comments about the assignments. Strongly recommended in my opinion.

The return to Calculus was very daunting for me but it's been a long time since I was in college.

Andrew does an EXCELLENT job explaining the equations and the reasoning for them. Just taking this course has already helped me make better decisions in my position at my company and has given me what I need to continue with new technologies.

Andrew is super organized in building both our conceptual and implementation knowledge of Deep Learning. Perhaps the time on basic Calculus could be reallocated to the Calculus of deriving formulae, which I did on my own. The assignments are designed flawlessly with well organized structure. Thank you for a 'deep' learning experience!

I appreciate this course, and the opportunity given to enroll in it through the financial aid. I can see the effort that was placed on proper instructions and consistency through the learning material. Thanks everyone at deeplearning.ai! You guys are exceptional and keep on imparting your knowledge on the world to make it a better place.

After a few days working on this course, I finished the final assignment and everything worked well. I thought this is absolutely useful for new beginners to learn about deep learning efficiently. Many thanks to professor Andrew Ng and TAs. Wish you all can do a good job and get much practical things from this course. One more thing

If you are looking for an introduction in Neural Networks, this is the course. Every class is focused in making you understand the basic theory related to the content, Andrew gives a strong focus on the linear algebra and calculus behind the content, and this helps you to understand why some decisions are made during the implementation.

I would like to sincerely thank coursera and the trainers for the beautifully designed Deep Learning course. It has helped me understand the basic mathematics behind the forward and backward propagations along with its implementation using numpy. Looking forward to invest more time in other coursers in this deep learning specialization.