AM
Oct 8, 2019
I really enjoyed this course. Many details are given here that are crucial to gain experience and tips on things that looks easy at first sight but are important for a faster ML project implementation
AB
Aug 26, 2021
Amazing course which focus on the theoretical part of parameters tuning, but it needs more explanation of Tensorflow, as I felt a little lost in the last project. Except that, it is an amazing course.
By Kiet L
•Aug 26, 2017
Another awesome course by Andrew. I wish he was my professor in my grad school. I hope Coursera publishes all the notebooks + data on public github so I can redo all the exercise again. Too much info to digest in short amount of time. I can't wait for RNN and CNN courses.
By Dan N M
•Jan 5, 2021
Excellent course. A great way to understand the fundamentals. It's always good to understand what's under the hood as frameworks abstract away a lot of the hard work going on underneath. Also makes you aware of how to be better tune and understand hyperparameters etc.
By Syed M H J
•Jan 8, 2019
Easily the best course on diving under the hood of how a Neural Network actually works and how to tune to the satisfaction of our results.
A no brainer for sure. The best part the exercises. You MUST do the exercises to understand thoroughly how the systems actually work.
By WAN L
•Aug 1, 2018
I like this course, it details basic while popular technique we need to optimize neural networks. also the lectures on different optimization algorithms are very helpful for you to know details on how they run when we choose these algorithm in frameworks like tensorflow.
By Akash M
•Jul 13, 2020
I found this course extremely helpful. It enabled me to develop a really good intuition about how deep learning models are made, and what are the small steps that go a long way in improving the overall performance of the system. I hope all of you find this helpful too.
By Arun G
•Mar 22, 2020
Excellent course, giving a very good insight into how to approach building a deep neural network, the concepts of various parameters, tips on how to best achieve a good algorithm and a step by step walk through of the different algorithms, parameters and optimization.
By Yash B
•Oct 22, 2019
Quite detailed curriculum. It is a great continuation for course 1 of this specialization series. As usual, Prof. Andrew Ng is there to guide our way throughout the course duration. A really fun and intriguing course which can lead to course 3 as a proper continuation.
By PeterStephenson
•Jun 26, 2019
This course was perfect for me. I thought it was a good balance between theory and practice. I don't think I'm ready to start building NN's from scratch, but at least now I know how to get started. Also, I now have an understanding of the complexity of a ML project.
By Shubham G
•Jun 18, 2018
Mini Batch/Adam Optimization concepts was very well explained. I was expecting the detailed derivation of the backpropagation for the batch normalization case. Overall it was a great course and it greatly improved my understanding about concepts used in deep learning.
By Favio A C
•Nov 3, 2017
4.5/5 A diferencia del primer curso que es una continuacion del de Machine Learning de Andrew Ng , aqui vemos una evolución del contenido , se pasa a ver miniBatch Gradient Descent, Regularizacion , Momentum , Adam , y un inicio a tensorflow
realmente un MUY BUEN Curso
By Huaishan Z
•Oct 1, 2017
Through the class, the tuning of Hyperparameter is detailed introduced and more important is that why it's tuned is very clear. Suggest persons study deep learning to study this class carefully.
Expect to have more info from the current study in University or College.
By John R
•Jul 24, 2019
I guess the difficulty is what you make of it, with further studying and dedication, but I would like to encounter more challenging assignments, where one has to code entire cells for instance, as opposed to a single line here and there.
But everything else is great!
By Janzaib M
•Mar 4, 2018
Contains very good understanding of Hyperparameters and their tuning process.
Secondly, teaches very well the mathematics of optimizers such as GD, SGD, GD with Momentum, GD with RMSProp and ADAM.
Finally, a small glimpse of Batch Normalization.
Highly Recommended!!!!!!
By Frank I
•Aug 25, 2017
I had previously used optimizers with momentum and variance momentum (Adam) with the understanding that they helped without knowing exactly how. This course cleared up all those tiny details and has left with with a greater appreciation of neural networks in general.
By Quentin M
•Aug 1, 2021
Although this particular course is not as sexy in its applications as the others it is still vital information for any serious practictioner. Prog Ng shares his years of experience and you really feel that with each video you are learning invaluable tips and tricks.
By Nguyá»…n V A
•May 29, 2021
This is an amazing course. I've learned a lot from this course, really amazing on how to tune these hyperparameters. I think this course would be a great course that you should have if you want to become an AI engineer! Thank Coursera a lot! Everything is amazing!!!
By Igor A G d O
•Sep 12, 2020
This was a great course. I could develop solid intuition about how neural networks work, and learn about state-of-the-art ways to make them better. The only thing that I have to complain about is the fact that the Tensorflow part should be updated to Tensorflow 2.0.
By Thomas N
•Oct 9, 2019
This course broadened my understanding of what really happens when driving the cost function closer to its minimum and techniques to go there faster. I found this course instructive and the programming excercises helped a lot to digest the learnings from the videos.
By saikiran k
•Aug 3, 2018
I know deep learning already, but I saw many people who even know it doing this specialization,so i too started like that..but its a very good experience concepts are very well explaining and I am enjoying assignments a lot it a very fun experience doing all again..
By Narek A
•Oct 8, 2017
I find this course very useful, many complex ideas are presented in a very understandable way! This course is like a collection of all important aspects! However, homework could be more difficult, because now almost all the answers are given in the python notebooks.
By Sagren P
•Sep 4, 2017
This specialisation is an exciting journey - can't wait to start the next course. The foundational concepts of neural networks are expertly packaged in these courses, together with enough practical exposure to get you started on a fun learning and career experience.
By MUHAMMAD A N
•Nov 29, 2022
This was the second course of my deep learning specialization. So far, I have been able to get a complete grasp on how to tune the DNN hyperparameters and apply different methods like regularization effect on your parameters to further improving the Neural Network.
By Akash K
•Aug 8, 2020
Best course to improve your understanding of Neural Network tuning, moreover the Tensorflow course at the end of 3rd week is really detailed, I worked earlier with tensorflow but didnt get its details accurately, but now I am confident enough about using tensorflow
By Neil S
•Jun 17, 2019
Wonderful course that teaches one the intricacies of training better models. It's also great when learning to implement a neural network through Tensor Flow for the last assignment and realizing that you have a good understanding of whats going on "under the hood".
By Andrey M
•Apr 9, 2020
This course is very thorough and detailed. Now I can clearly and confidently say that I can perform good research and obtain formal information and data on any topic, as opposed to just surfing the internet for genuine knowledge. Great course, well done to Andrew.