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Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization(으)로 돌아가기

deeplearning.ai의 Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization 학습자 리뷰 및 피드백

40,598개의 평가
4,318개의 리뷰

강좌 소개

This course will teach you the "magic" of getting deep learning to work well. Rather than the deep learning process being a black box, you will understand what drives performance, and be able to more systematically get good results. You will also learn TensorFlow. After 3 weeks, you will: - Understand industry best-practices for building deep learning applications. - Be able to effectively use the common neural network "tricks", including initialization, L2 and dropout regularization, Batch normalization, gradient checking, - Be able to implement and apply a variety of optimization algorithms, such as mini-batch gradient descent, Momentum, RMSprop and Adam, and check for their convergence. - Understand new best-practices for the deep learning era of how to set up train/dev/test sets and analyze bias/variance - Be able to implement a neural network in TensorFlow. This is the second course of the Deep Learning Specialization....

최상위 리뷰


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


Dec 24, 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\n\nThanks.

필터링 기준:

Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization의 4,258개 리뷰 중 4151~4175

교육 기관: Joao N

Nov 05, 2019

One again the course is a great follow up from the previous one. The only little detail I wish had been done was for the assignment to cover a scenario where we had to improve some hyperparameters by applying different approaches covered in class.

교육 기관: Gilad F

Nov 03, 2019

I'd make the tesnsorflow section a separate week with much more elaboration, the first time (in both course 1 and course 2) I felt a subject was lacking information. It's mostly noticeable in the programming assignment.

교육 기관: Fabio S

Nov 04, 2019

Suggestion of references, as a complement, would be very interesting.

교육 기관: Marcos C D

Nov 03, 2019

Content needs update to leverage the state of the art in the subject.

교육 기관: Jörg N

Oct 19, 2019

I liked the course a lot and I really adore the way Andrew Ng teaches the subject. As an improvement suggestion I would extend the course to four weeks to deepen the practice on Hyperparameter tuning as well as the introduction to Tensorflow. The Programming exercises of week 3 were really challenging. First since there were partially misleading statements in the comments (Z before activation) and second because variables were given the same names as tf parameters and partially even function definitions. So you could see things like a = a, b = b in tf function calls which just does not fit for beginners in portentously both Python (local variables concepts, etc.) and TF. I am more than grateful though that I could do this course of the specialisation and I would really like to express my deep gratitude to Andrew Ng.

교육 기관: Ansgar G

Oct 17, 2019

Andrew Ng is great again. Also the assignments are good with very good explanations for each step in the notebooks. The TensorFlow programming assignment at the end could have gone a bit deeper, with more explanations for things that are used in the end like eval. And it had an error as the third parameter of tf.one_hot is not (anymore?) the shape. You have to explicitly pass it as tf.one_hot(indices, depth, shape=shape).

교육 기관: Mihaly K

Nov 06, 2019

Assignments sometimes too easy, minimal input needed.

교육 기관: Mohamed S

Oct 20, 2019


교육 기관: Thibault C

Nov 07, 2019

more intuitive insights would be helpful

교육 기관: Charles H

Nov 08, 2019

The lectures are all really good, but the programming assignments feel like they hold your hand too much. It's very easy to sort of slide through them without having a good understanding of the material.

교육 기관: Mustafa S Ç

Oct 22, 2019

Everything was great. Every peace of information scratch in my mine. I learned a lots from course.

In the last part; Tensorflow has dramaticly changed but content didn't renewed.


Oct 23, 2019

Good but need to improve number of examples about tensorflow

교육 기관: Huy T T

Dec 04, 2019

Overall, it's pretty good. I did have a problem understanding some of the facts being communicated about gamma and beta in batch norm. Also, I think there is a problem with the last notebook. My cost did not go down as fast.

교육 기관: אוריאל ב

Dec 05, 2019


I enjoy the course a lot!

for tensor flow - I am not sure if its me or the course - but I need much more training to start thinking the tensor flow way. maybe i will practice more on real work cases.

thanks !


교육 기관: Vikash C

Jan 28, 2019

Content was good.

But the system that checks our submitted our code checks wrongly even when I wrote it correctly.

In week 2 assignment, when I submitted the code, it gave many functions as wrong coded.

I resubmitted the code after few changes, for instance a+= 2 changes to a = a+2 and string text like 'W' changes to "W". It worked fine and gave 100 points.

In short, what I observed is that the code checking system is taking a+=2 and a=a+2 as differently, also 'W' and "W" are considered different, but they are not in actual output.

교육 기관: Kartheek

Feb 01, 2019

week 3 topics would have been a bit better

교육 기관: Amit C

Feb 01, 2019

I wish the course mentors were more active on this course makes it a bit difficult to clear doubts

교육 기관: Tan K L

Jan 26, 2019

I think more should be done regarding the TensorFlow framework with more explanations given to what the functions did

교육 기관: Morisetty V A S K

Jan 20, 2019

Interface for evaluating is not great and assignments are easy

교육 기관: srinivasa a

Jan 09, 2019

its great foundational course but i feel with frameworks available the math behind it was little boring.Andrew NG is pretty good with explaining it well but sometimes felt it was too trivial

교육 기관: Long H N

Feb 13, 2019


교육 기관: zhesihuang

Mar 03, 2019


교육 기관: Till R

Mar 02, 2019

Exercises are too easy, and lectures are kind of boring. The Jupyter / iPython system does not run smoothly. I ended up downloading everything on my local computer, completing the assignment there, and then pasting the code into the coursera notebook. That makes the assignments take 50% longer than necessary.

교육 기관: Jorge G V

Mar 07, 2019

The lessons are good, the programming assignment has mistakes that have apparently been reported over a year ago and have yet to be fixed - there is no excuse for this to be the case.

교육 기관: Ilkhom

Mar 21, 2019

awful sound