CM
Dec 23, 2017
Exceptional Course, the Hyper parameters explanations are excellent every tip and advice provided help me so much to build better models, I also really liked the introduction of Tensor Flow
Thanks.
NA
Jan 13, 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.
By Dário P
•Mar 18, 2020
Nice basics that help understand the fundamentals. The last part of the course should be upgraded to Tensorflow 2.0 already...
By Uddhav D
•May 28, 2019
Again awesome explaining by Andrew, although I feel Batch Normalization should be a bit stressed upon and explained in detail.
By Tarun S
•Sep 18, 2017
Well detailed course..
Tensorflow is very basic and it could have been improved if one can visualize graphs too in tensorboard
By Pranay V
•May 20, 2020
Explains neural nets like a tutorial more than a formal course. Overall pretty insightful. Also, instructor can speak louder.
By Steven A
•Nov 7, 2017
Great course!! The only improvements I'd suggest is more difficult assignments (less guided) and more written documentation.
By Bruno C
•May 7, 2023
Maybe i was doing it wrong but the last tensorflow exercice add me buggin. Tried everything and it didn't worked as expected
By Shashank K
•Oct 15, 2020
Some of the best intuitions behind Neural Networks can be provided by none other than Andrew Ng and this course proves that!
By Kevin M
•Sep 24, 2020
Very good - wouldve been more effective if included the questions part way through the videos as previous courses have done.
By Jonathan G
•Aug 9, 2020
Es necesario que actualicen los notebook por ejemplo el de TensoFlow ya que esos códigos no corren bien con la nueva versión
By Alonso O O
•Apr 7, 2020
This course was a little bored for me. I already knew a little bit about hypertuning so I felt that the course moved slowly.
By Omar S
•Oct 29, 2017
Provides a good code skeleton to build a neural network, but would unlikely have one poised to do improvements on their own.
By Nikolaos P
•Nov 29, 2021
Very good course, but I would expect some hands on hyperparameter tuning (using maybe an additional programming assignment)
By Kevin C
•Oct 28, 2020
Está bueno el curso pero quizás lo más interesante sea el uso de TensorFlow al final para que todo empiece a tener sentido.
By Om S P
•Jul 19, 2019
Some assignments, even though I get the same result as the output given, it get marked as wrong... Please try to rectify it
By Victor P
•Oct 26, 2017
Very good course from the excellent Andrew Ng.
Some typos and some glitches in the video, hopefully it will improve in time.
By Alex N
•Sep 12, 2017
Good pace
Only drawback is that some of the safe checks are wrong in the programming assignments, even with the right seeds.
By Khalid A
•Sep 14, 2019
It is definitely very informative, but I wish the lectures would be more in depth in regards to the derivation and proofs.
By Ruud K
•Feb 6, 2019
Really love the course, the quizes and programming assignments. But not 5 stars cause the audio quality is extremely poor.
By Leandro R
•Jan 25, 2022
Very good course. It would be 5 stars if it had questions on each video and a bit more difficult programming excercises.
By Arkosnato N
•Nov 28, 2017
course content was very good, but this course should be longer. there was a lot of material covered in a very short time.
By Michael B
•Mar 17, 2018
More pragmatic approach with theorems would be more appealing....or maybe it is me as i'd prefer Java (DL4J)...not sure
By Santiago F V
•Jul 2, 2020
The theorical part is perfectly explained. However, the program assingment of the las week is not as good as expected.
By Nguyá»…n Q T
•Jun 21, 2020
Thanks a lot for clearly explaining of intuition about algorithms and optimizer. More ever, great design of assignment
By Avinash V
•May 4, 2020
Outstanding material. Would like to thanks Mr. Andrew Ng Sir for providing such a nice and detailed description.
THANKS
By Vivi M
•Oct 29, 2017
I really enjoyed the classes, in the training I would've liked to try and improve the model with all the tools learned