Jan 14, 2020
After completion of this course I know which values to look at if my ML model is not performing up to the task. It is a detailed but not too complicated course to understand the parameters used by ML.
Oct 09, 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
교육 기관: Peter T•
Apr 17, 2018
Useful information, good intuition, but lack of formal results. More homework would improve the learning experience.
교육 기관: Ashutosh P•
Apr 04, 2018
It was a great course. Really well taught by Professor Andrew Ng. Some "from the scratch" coding assignments needed.
교육 기관: Suresh D•
Mar 01, 2018
I hated the tensorflow part though. Would have much preferred it if we could have moved away from jupyter notebooks.
교육 기관: Francisco C•
Jul 24, 2018
Very good content overall. Very well explained and good examples. Many mistakes in the comments in the assignments.
교육 기관: Abhinava K•
Dec 08, 2017
Content is good, but assignments are not interesting. Some application oriented assignments will be be encouraging.
교육 기관: Manish C•
Jan 23, 2020
Like all other andrew ng courses this course is also the best course to deep dive into neural network algorithms .
교육 기관: Francesco P•
Feb 26, 2019
I would like to see more programming assignments. They are very well done and it'd be great to have more of those.
교육 기관: Angad P S•
Dec 13, 2017
I would really benefit from this course if more assignments are provided to try different data sets and scenarios.
교육 기관: Giovanni C•
Feb 11, 2019
I liked the course, but the explanation of tensorflow needs more propaedeutic introduction for a learner like me.
교육 기관: Charbel J E K•
Jan 17, 2018
Really helpful ! Too much concepts to understand but only applying few in the course. I really liked this course.
교육 기관: Jay R•
Dec 24, 2017
Good course to get familiar with hyperparameters and improving the neural networks. And cliff hanger was amazing!
교육 기관: Mads E H•
Oct 26, 2017
Nice and practical. The assignments could go a step further in trying out different things to get better results.
교육 기관: Jayanthi A•
Apr 05, 2018
It was great course, however, I would have liked it to be a lot slower with more time being spent on Tensorflow.
교육 기관: Joshua S•
Nov 13, 2019
A good course that provided more intuition on which models to work with and how to tune parameters effectively.
교육 기관: Aayush A•
Aug 03, 2019
The Jupyter notebooks had a lot of mistakes which wasted a lot of my time otherwise the course content was good
교육 기관: Corbin C•
May 10, 2018
Good lectures, but the jupyter notebook examples are inconsistent and sometimes use deprecated Tensorflow code.
교육 기관: Srikanth C•
Oct 01, 2017
I particularly benefited from the explanations of dropout, batch normalization and the RMSProp/Adam optimisers.
교육 기관: Narendran S•
Oct 01, 2017
TensorFlow needs more time dedicated to it. I didn't completely understand the concepts behind this framework.
교육 기관: Arun J•
Sep 17, 2017
really loved the course material but would have loved it more if it gave more in depth tutorials on tensorflow
교육 기관: Hector D M P•
Sep 02, 2017
Nice and clean; with nice focus in the framework; but they also could be more in depth regarding the exercises
교육 기관: Raman J M•
Aug 20, 2017
Quizes as part of middle of lectures help to check the understandings. For many lectures quizzes are missing.
교육 기관: Yunhao Z•
Mar 21, 2018
-1 : Serveral bugs inside the assignments, causing 0 grades in auto grader
That said, a perfect intro to DNN.
교육 기관: Qihong L•
Oct 02, 2018
sometimes the teacher speaks too fast to follow, but the content itself is very good and easy to understand
교육 기관: Gustave G•
Dec 23, 2017
Very good videos but programming exercises are way too easy and some written material would be appreciated.
교육 기관: Donguk L•
Nov 25, 2017
Maybe providing some video or reading resource for back propagation processes for batch norm would be good?