Great course, Andrew Ng is just the best teacher for NN and machine learning. Assignments and quiz too easy, probably i will struggle on the implementing it on my own. But is common to MOOC so definitely the best deep learning MOOC out there

I wish these assignments would never get completed. Very nicely hand holding done through out the assignments so that you don't loose interest and also teach the intended stuff without watering down.

Thanks a lot! Recommend this course highly!

I'm a beginner in ML so i don't know much to say but this course teaches what it says it will do. In the middle of the course you may be having lot of questions about how it all fits together, but they almost always get clarified in the end.

Dear Committee of Coursera,

I wanted to take a moment to express my gratitude for the incredible support I received throughout my learning journey.

The support that I received from Coursera was commendable and I just want to say: Thank you

A LOT OF INTERESTING CONTENT

A lot of content to improve the knowledge about NN and related frameworks! As always a lot of guided interesting practices very applicable to real problems. I will continue with the rest of modules without doubt.

A bit hard to follow but worth the time spent as this course helps to build the intuitions behind some of the most famous optimization algorithms and tuning methods by making the students work through them using only basic python and numpy.

Very practical course for implementing deep neural networks from scratch. The ideas of hyper-parameter tuning, regularization and optimization are very refreshing even for experienced deep learning engineers. Learned a lot from this course.

The course was really interesting and helpful! This series of coursers guides even a novice to the field through a simple, easily understandable learning process. Many thanks to Coursera, DeepLearning.Ai, and the lecturers for this series.

Continuing the trend of magnificent course content, Dr. Andrew Ng walks us through some exceptional practical advice in implementing DL algorithms, detailing the concepts and the best-practices, and mentioning the pitfalls. Simple awesome!

It's a very good course for those willing to dig into the nitpicking of it. If you're really serious about this field, or if you're going to use neural networks often in your job, these lectures (and notebooks) can save you a lot of time.

This is an excellent class for understanding how to tune neural networks. I guess this will continue to be a valuable skill set until we have neural networks that can figure out optimal parameters to design and tune other neural networks.

I've worked with deep neural networks before for a while, but this course gave me a lot of new ideas, especially different tips and tricks on fine-tuning hyperparameters and speeding up the training of a deep neural net. Highly recommend!

Very good follow-up course to the NN basics and well explained/covered by the instructor. I am already a big fan of Andrew - enrolled the course with positive feedback about him and the courses and their quality exceeded my expectations.

The course is okay. The programming assignments really shows how tuning the equations improve neural network. At the end there is a quick introduction to Tensorflow. It's too shallow but I guess rest of specialization will teach me more.

Pretty much helpful. I was a novice and this course helped me a lot to start my jourmey in a right way. I will recommend others to come and join this course and hopefully you all can get more insights in your career in machine learning.

This course provides a lot of insights towards improving performance and accuracy of deep NN with clear teaching, step by step and practical assignments. Love the introduction of TensorFlow in this course. Hats off and thank you so much!

Great continuation of the 1st course of Neural Networks where you explore more about NN and how to optimize the implementations / algorithms. This course explains again at a lower level grade how the hyperparameters affect the algorithms

The introduction to Tensorflow and real tools to work with these complex aproaches is something I did not expect and is really good. It more accessible than the previous one ! And that makes it more applicable. I am happy with the course

Tuning is very important piece in DL. Thanks for this awesome course prof Andrew! A little peak into Tensorflow is quite eye-opening. Though it's only Tensorflow 1.0 but you will come to know later how powerful Tensorflow 2.0 has become.

This part is one of the most important to working with NN or DL nets. The instructor has achieved to teach a not so easy topic in an awesome manner so everyone is able to tune his networks as a professional. Can't wait for the next part.

I this course I learned how to improve Deep Neural Networks by applying different methods that help to speed up the convergence and to reduce overfitting. Also, now I have some basic knowledge about using TensorFlow. Thank you very much!

Exceptional Course. I really enjoyed the explanation of Hyperparameters. Every tip, every piece of advice helped me to build better models. Moreover, I liked the introduction part of the TensorFlow framework. Thank you, Prof. Andrew Ng.

pretty good course all in all !, I would say considering the difficulty of this topics, the instructor has done a great job in transmitting the relevant parts that one needs to remember and also in justifying why things are as they are.

Very well structured class as a follow-up to the first one. Heavy on information but this is a good thing. As someone who isn't pro at Python, the development part was much smoother since programming wise it is similar to the first one.

En línea con los anteriores. Muy teórico pero perfecto para entender los entresijos del funcionamiento de los algoritmos. Si acaso echo en falta algo más de tensorflow pero supongo que se verá en el resto de cursos de la especializacion