AS
Apr 19, 2020
Very good course to give you deep insight about how to enhance your algorithm and neural network and improve its accuracy. Also teaches you Tensorflow. Highly recommend especially after the 1st course
AM
Oct 9, 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
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 10, 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 8, 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 15, 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 22, 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
By Amit J
•Nov 22, 2019
Great practical insights.
I wish there were programming assignments on "Hyperparameter tuning" and "Batch norm" too.
By Christopher S
•Oct 25, 2019
Good intro to the available tools. Very guided course. For concepts to really stick, own projects or courses needed.
By George L
•Oct 24, 2018
it's good, but definitely not as good as the first course since Prof. Ng was not very clear on some of the concepts.
By Ruixin Y
•Apr 30, 2018
The course itself is great, but the notebook (programming assignment system) is not stable, it's annoying sometimes.
By Péter T
•Apr 17, 2018
Useful information, good intuition, but lack of formal results. More homework would improve the learning experience.
By Ashutosh P
•Apr 4, 2018
It was a great course. Really well taught by Professor Andrew Ng. Some "from the scratch" coding assignments needed.