Excellent course. This help me a lot for my Masters research. Thank you so much Coursera for the financial aid you offered me for this course. It really helped me a lot.

This is indeed a very good course. It helps me understand what the parameters are and how to tune them. Very practical and intuitive. Thank you again all my instructors.

Gran curso! Te enseña a comprender que los hiperparámetros no son solo números con los que jugar, sino cuál es su sentido y cuáles son prioritarios (entre otras cosas).

This might not be the best curse . in the world, but it is doubtlessly the best one in my mind. Thank you, Dr. Andrew! Thank you, Coursera! Also, many thanks to Github!

Este segundo curso de la especialización fue realmente provechoso. Muchos de los conceptos que se manejan resultan vitales para lograr desarrollar buenos modelos de AI.

Again, a very structured course with Dr. Andrew Ng being so calm and simple explaining all methods of the course. It was worth my time! Many thanks to the organizers :)

Very nice materials. The self-contained Jupyter Notebook is nice in that it doesn't require local installation. However, it kept crashing. I'd much rather code locally.

Today i have finished the 2nd course. It was amazing a lot of things to learn and still looking for the remain 3 courses of deeplearning.ai. Thanks to the coursera team

The challenging concepts therein the course were well-explained & simplified. Also the Assignments gave a decent chance to brush up the concepts learnt while lectures.

Leaned how to tune the required parameters and hyperparameters in different scenarios which is a big help. Hope to implement the learning and continue to third course.

Andrew Ng is the best for explaining "What 's going on" on every single lecture,if you didn't understand ,search it ,it will help you to survive :D,Enroll THiS CoUrSe

Extremely nice the course, very useful and easy to master. Only thing is that the model of the final work is really not good enough. I tested five gestures, all wrong.

The course helped me gain a clear perspective on how to make my Deep learning model improve in performance and accuracy. The teaching was clear and precise. Thank you!

Really great introduction to deep learning. Made the use of frameworks such as Tensorflow easy to understand through guided implementation of deep learning using Numpy

It course contains best opportunities to learn how work with your Neural Network and how to adjust parameters. So far, this is my favorite part of this specialization.

Really impressed with this course....Andrew is one of the best teachers I've ever had and his Deep Learning course is one of the best courses I've taken from Coursera!

This course is helpful because they taught the fundamentals and the intuition that goes behind tuning methodologies instead of going straight to the technical portion.

Great course! The only little thing was that submission grades of one assignment were broken and few things could be polished in this course. But overall it was great.

Really nice to go into the basics of some of the most used optimizers and regularizers currently being used. Also nice to have an intro into the basics of TensorFlow.

Excellent course with great learning materials and tests. The sample code provided in the programming assignments is a great starting point to amazing implementations!

I knew all of these but the detail and why it was needed is not explained in most places. This specialization is best place to get the holistic view of deep learning.

Amazing course to understand verious concept of Hyperparameter tuning and optimization. Regularization concepts are very well explained and helped me to learn a lot!!

Very well taught by making simple explanations for various complex algorithms. Hope Tensorflow was taught more deeply as only the surface of it has been taught here .

Very recommended, even though the exercises can be passed without really understanding, they are very well explained and if you want to, you can learn lots from them.

The course content is of adequate depth and sets a good base for us to start applying DL in our projects. A project component can also be added to make it even better