Oct 31, 2017
Thank you Andrew!! I know start to use Tensorflow, however, this tool is not well for a research goal. Maybe, pytorch could be considered in the future!! And let us know how to use pytorch in Windows.
Dec 06, 2019
I enjoyed it, it is really helpful, id like to have the oportunity to implement all these deeply in a real example.\n\nthe only thing i didn't have completely clear is the barch norm, it is so confuse
May 30, 2018
This lectures + programming examples are very good for a kick start and to understand key concepts. I'm a mathematician, diving into deep learning. I really appreciate this course. The programming examples are valuable even if my python knowledge is on a beginners level. Thanks!
By Dipanjan G•
Feb 03, 2020
This again is an excellent insight on the hyper parameters and deep learning frameworks. The extreme prowess in the subject but at the same time a very lucid and relaxed style of teaching from Andrew helps quickly grasp these difficult concepts. Looking forward to much more!!!
By RAGHAV S•
May 25, 2018
This is such a crucial course to build upon the fundamentals of Neural Networks.
Especially the intuitions that Andrew has provided really add to the arsenal, I'm so glad I took this course.
Looking forward to the other courses in this specialisation.
Thank you Andrew/Coursera :)
By Erik E•
Oct 02, 2017
This is a great course!! In this course a lot of the previous concepts start to be refined and streamlined for efficient implementation. I feel like this course gave me a better handle on the concepts that have been building since my first Machine Learning course by Andrew Ng.
By Dishant G•
Sep 28, 2019
Very well explained each and every concept only I had struggle in gradient checking and every other video and quizzes are great. I hope after doing these courses I will definitely get a good career start after my graduation.
Andrew Ng Sir is Greatest teacher I have found yet.
By Miguel P d L•
Nov 26, 2017
Excellent course, even using intuitions Prof. Andrew Ng is able to communicate the very details of the different regularization approaches, as well how to do a good hyper-parameter search. Finally it introduces the TensorFlow framework with a very nice programming assignment.
By Yang Z•
Dec 15, 2019
This course gives learner a high level strategy in tuning hyperprameter. It teaches me not only the knowledge but also the intuition about the processes. It is also great to learn how to use Tensorflow framework in training models. Great job deeplearning.ai team and Andrew!!
By Kai-Peter M•
Oct 28, 2019
Great course!!! The best online course I have ever taken! I enjoyed almost every day I participated in that course, really an educational treasure! It is so comprehensive and detailed at the same time. Due to the good presentation of the topics it was really understandable.
By Mandar K•
Jul 22, 2019
Wonderful course and material. Andrew has a great way of explaining the topics in the simplest way. Although I had some issue with understanding the optimizers, I learned a great deal. However, This course needs a revamp using Tensorflow 2.0 for the tutorials :) Thank you
By Amit G•
Nov 06, 2017
there is a lot of materiel that is being discussed during the lectures, and all of it seems like it could be really relevant. I am missing a consolidated course deck - ie something like a deck of slides on all the important concepts that are being discussed, for reference.
By Kiet L•
Aug 27, 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 Syed M H J•
Jan 09, 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 01, 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 Yash M 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.
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 03, 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 01, 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 04, 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.
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 Thomas N•
Oct 09, 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 03, 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 08, 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 04, 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.