The way of teaching The "Andrew Ng" is just incredibel he is not just a instructor he is my mentor in th field of ML and DL or I can say tha in the field of AI envery topic he teach with very easy to understand and material was updated and easy to understand and Lab workspace was also good

Took the course to retest my knowledge in Deep learning. Have completed this course some time back. Without certificate. Professor has covered each of these topics in good detail. Practice workbooks and assignments are really helpful and provide a great start for deep learning enthusiasts.

Really like the assignments in this course, which gives me hands-on experience with advanced knowledge such as Adam optimizer, gradient checking. Tensorflow v1 assignment is also good, but I am not sure whether API is still relevant as Keras based API for tensorflow v2 is already released.

With this course, even the beginner can understand why what happens when tuning and optimizing a neural network model. With easy to understand methodology and great explanation, I highly recommend this course for anyone who wants to go deeper into deep learning and understand the workings.

Very helpful learning material.

I'm still a bit confused though, even after passing the exams and exercises, but I think its mostly because I've lost grasp on mathematics. So, the blame is on me not coursera.

Hopefully I would fit more in the Deep Learning world by finishing up the course ;)

This is a great course and you get to do real programming and training of a Deep Neural network. Andrew Ng is an excellent instructor. The final assignment wasn't hard but the syntax was difficult to follow. Using the forum and the Tensorflow documentation you can make your way through.

This builds on the basics from the first course with some important techniques (such as Xavier initialization, Adam optimization, and batchnorm) and ends with an introduction to implementing these in TensorFlow. Fast-moving but well taught with a good mix of theory and hands-on exercises.

Awesome course. Theory and practise in the right proportion. Programming assignments are useful, interesting and use modern technologies like Python or TensorFlow. Question quizzes are not too hard but help to repeated theory. Also, I liked interviews with great people from Deep Learning.

I am totally enlightened by this course. A lot of the concepts covered were completely new to me and very helpful in building a good performing neural network. The lectures were in depth and very well organized. The contents are not something you will come across in other tutorial sites.

A great refresher to Andrew's original ML course at first, but also later is learning current deep learning current mindset at work. Great pace, great course, and great programming assignments. Makes me want to see the 3rd course for (i hope) more challenging programming assignments :) .

Gave me a clear understanding on how to improve the calculus on a neural network. Computational software has advanced from programming in R of Python to software frameworks, hiding a lot of the math. Needs another study of the software frameworks though!

Thanks for the opportunity to join.

prof. Ng's teaching was so great. some tricky details taught that I never considered them before. when I read the textbook, it was easy to understand and repetitive. I've learned simple and clean implementation. in overall it was important, simple, understandable, time efficient course.

A very well structured course on some of the most overlooked (but critical) elements in Deep Learning. Prof. Andrew Ng definitely makes everything seem easy; he breaks down even the most complex of optimization algorithms and explains it with sheer simplicity. Would definitely recommend!

Course has been designed so well that even a aspiring beginner can learn the concepts very well.

Every student who wants to begin their career in the field of Deep Learning must follow this course.

Especially the tensor flow concept is taught very well with the help of exercise tutorial.

Thank you Andrew and Team for this course. I must say the course has surprised me and I have myself surprised my level of learning. But all credit to the way course is laid out and the step by step method of progress along with strong conceptual explanation helps a lot. Thank you again

This specialization course gave me a better understanding of hyperparameters and the process of tuning them. Learning new information will help me build my own project without unexpected results. Andrew Ng still gives better intuition. I really appreciate the materials in this course.

An excellent course by Andrew about how to improve deep learning models. I actually thought about something over-emphasized before taking the course, but after completing it I have changed my mind completely: THIS COURSE IS A MUST IF YOU SERIOUSLY WANT TO GET INTO DEEP LEARNING WORLD!

Awesome Course! :)

Andrew is really the best instructor... He makes problems very easy to solve.

The content is fantastic...

The best part of this course is Optimization algorithms.

I loved every video and content with best explanation on hyperparameter tuning...

Adam optimization is best

A great course, with deep understanding of all important hyperparameters and the related concepts important to tune the deep neural networks. Lectures are up to the mark and so are the programming assignments. Thanks a lot Andrew Ng and Coursera for making it possible for me to learn.

As usual, another incredible course taught by a really good teacher. I strongly recommend it to anyone who wants to get a firm garsp about optimization algorithms and how they really work, apart from hyperparameter tunning and regularization methods for bias/variance. Thank Andrew Ng!

Very helpful in building on the foundation in neural networks and deep learning with practical experience. The programming assignments are reinforce key concepts and are a great asset to keep after the class and apply in projects. Andrew is doing great work bringing AI to the masses!

Nice illustration of the tricks including Batch-Norm, Optimization as well as Dropout, etc. Sometimes the lack of the theory is sort of unstatisfying, but considering the difficulty of a comprehensive intro for all of the above, it has been good enough for beginners to catch up with.

While the first course in the specialization is the perfect introduction to the realm of NN, this course is the place where I learned to implement a true Deep Network. It talks about various optimizations and parameters of the DL models. Bonus, it introduces the tensorflow framework.

Great course! Very well laid out approach to tuning a deep neural network. FInal introduction to Tensorflow was useful, but I think a lot of information was compressed into a single video. Suggest spreading this a little more. The Tensorflow programming assignment was pretty good.

Genial curso en el que aprender como optimizar tu red modificando una serie de parámetros y usando diferentes algoritmos. Ademas genial introducción a Tensorflow con el que avanzar en el montaje de redes de manera rápida. Recomendado totalmente tras realizar el curso anterior a este.