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 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.
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?
교육 기관: Aaron E•
May 05, 2019
its a good intro, if not a little simplistic with the coding exercises, bring back the quizzes mid lecture
교육 기관: Oleksiy S•
Dec 11, 2018
A small validation output error that is still not fixed prevent to rate all stars for the exellent course.
교육 기관: 苑思域•
Aug 03, 2018
This one is actually a little bit better than the first one, maybe less content, maybe more understandable
교육 기관: Leitner C S E S•
Aug 29, 2017
Excellent course. But -1 for using TensorFlow, a not-really-free framework, to introduce students to them.
교육 기관: Jayshree R•
Jul 04, 2019
An intuitive approach towards Hyper parameters. Covers the concept of optimization algorithms quiet well.
교육 기관: Makragić A•
Jan 09, 2019
Great lectures, I'm little disappointed with TensorFlow tutorial, there should be 1 week for that only...
교육 기관: Richard H•
Sep 29, 2017
Fills in the tricky gaps in using DNN that are necessary to transition from basics to practical projects.
교육 기관: Shijian G•
Nov 29, 2019
These series are generally clear and well-organized. It would be better to provide tensorflow materials.
교육 기관: Ranjan D•
Jul 17, 2019
Great explanation on tuning different hyper parameters and how they can effect the model's performance.
교육 기관: Keanu T•
Jun 26, 2019
I wish it went a little more in-depth with softmax classifiers but I can find that online so it's good.
교육 기관: Byron M•
Apr 09, 2018
The final assignment didn't have the right instructions, a lot of misleading comments and instructions.
교육 기관: Matías L M•
Oct 30, 2017
The professor is really good at explaining. The projects got more interesting than in the first course.
교육 기관: Per K•
Oct 03, 2017
Get you to a more practical understanding of deep learning. The introduction to TensorFlow is valuable.
교육 기관: LEO L•
Jul 31, 2019
All is good except the submission part, sometime return submission failure without specifying a reason
교육 기관: Hamza E B•
Jun 22, 2019
Great Course ! I learned a lot, but I would have preferred another Framework though (like Pytorch) ...