Would have been 5 star but I found typos in the assignments and exercises -which have still not been corrected which is quite surprising

Good course overall . The batch normalization explanation were not so convincing. The last assignment on Tensor Flow need improvement.

The course is nice but the tensorflow exercise has a lot of functions that weren't explained before and implementing them was difficult

Its good hands-on course but to master it will certainly requires to dwell more into the specifics and need to work on various projects

Was a great course. Learnt conceptually and implemented Momentum,ADAM & rmsprop. Wish there were more exercises to explore TensorFlow .

I would have liked more programming exercises related to regularization and hyperparameter tuning, but TensorFlow was well introduced.

Weeks 1 and 2 were awesome. However I think we ned a more intensive programing assignment on Week 3 to get hands on with Tensor Flow.

I liked the course. I just think there should be more assignments. Perhaps after each week because the content is dense and complex.

Too much spoon feeding in the programming exercises, could have asked us to make a model with atleast x accuracy then left us alone.

This was the toughest course since lot of mathematical, especially statistics back ground is required. However, I could complete it.

The course includes lots of information and need focus and concentration.

The Tensorflow part is not enough to solve the assignment.

Its require basic python programming for implementation of neural networks , different models techniques to get perspective of it .

One of my best courses i have ever participated in, i gained a lot of knowledge and knew the underlying mathematics of every model.

Second step of the specialization,

a bit less rewarding than the fist course as more fine tuning and less overview of deep learning

Programming assignments could have been more challenging. Otherwise, the course instructor is pretty awesome!! Thank you Andrew Ng.

Good material and definitely essential in order to gain a lot of time aiming at the right direction navigating all these parameters

Very good course. I would have liked a little longer introduction to the tensorflow architecture and less help on the assignements

A good introduction to gradient descent algorithms and hyperparameter tuning with a little TensorFlow thrown in for good measure!

Good course, Hyperparameter tuning, Regularization and Optimization are well explained, and the Tensor Flow lab is very useful too

Es un buen curso, basado principalmente en aspectos prácticos. Me pareció menos interesante que otros de la misma especialización

Tips are very useful! Have some typos/errors in assignments, more coding work can help understanding. Thanks for sharing, Andrew!

Many practical tricks such as tuning hyper parameters and the use of major optimization techniques such as batchnorm and dropout.

I think a bit more hands on teaching would be better for this course and also if you could mention resources it would be better.

Bastante bueno, explica de manera simple y práctica los distintos métodos para acelerar el aprendizaje de las redes neuronales.

The last assignment has no clear instructions on how to use the functions and has error which doesn't initazlie the parameters