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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

4.9
43,137개의 평가
4,638개의 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

XG

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.

AM

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

필터링 기준:

Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization의 4,572개 리뷰 중 4076~4100

교육 기관: Jérôme B

Dec 11, 2017

This course made a lot more sense to me, compared to the first one. Still a bit excessive on calculus in my opinion, but I guess calculus makes more sense for other people.

교육 기관: KUMAR M

Feb 09, 2020

A great course to learn how to make our deep learning models better. The flow of the course is superb. The only thing I felt can be improved was the level of assignments.

교육 기관: Minha H

Jan 01, 2020

Good coverage of practical issues in hyper-parameter tuning, regularization, and optimization of algorithms. Would be better if it covers TensorFlow 2.0 (instead of 1.0).

교육 기관: Bahadir K

Aug 23, 2017

couple of problems in notebook files (especially in the last homework) wasted my time, but it was a great course and to understand the math behind and learning tensorflow

교육 기관: Nazmus S

Apr 02, 2019

Learning a lot. But full of boiler plate codes. It would be great if students were challenged with programming. Writing a formula even in code is easy for most students.

교육 기관: Alfonso L R

Jan 07, 2018

I would like to have a brief introduction to Tensor Flow or a simple beginners tutorial (at least to have it clearer the usage of variables, constants and placeholders)

교육 기관: Jason D

Dec 14, 2018

These course really are 5 star learning but in terrible terrible need of video editing. We see outtakes, we see all three takes Andrew took to try to say something.

교육 기관: Robert P

Nov 29, 2018

Some issues saving my Python code. I'd complete and submit or complete in part and return and my work would not save or I'd get marked incorrect in the assignments.

교육 기관: Nishul S

Oct 10, 2018

Excellent course.

Shame about the total lack of support available for questions about problems I encountered. When I am paying for something, I expect some support.

교육 기관: Lian L

Nov 08, 2018

Great introduction to the tuning options for Neural Networks. Would have loved more visual representations of how different options affects learning and accuracy.

교육 기관: Wes H

Feb 13, 2018

Some oversights in programming assignments and the week by week content is not very balanced in terms of effort/time spent. Otherwise, I would have given 5 stars.

교육 기관: Julian K

Jul 20, 2018

Introduction to tensorflow was kept a bit too short for my taste and the coding part was mainly copy pasting the instruction text from above, making it too easy.

교육 기관: Keith S

Oct 02, 2017

Great course - Some small typos in the programming exercises and the Tensor video felt a bit rushed (needs 1 more video or lengthier explanations would suffice)

교육 기관: Thiemo M

Sep 01, 2017

A big step forward to understanding how to tune neural network performance. Didn't learn all of this even through a couple of years of trial and error on my own

교육 기관: irfan s p

Feb 21, 2020

good course, but unfortunately different with network and deeplearning course, that has fast response mentor. But all in all the course is full with knowledge

교육 기관: Kate S

Mar 07, 2018

Excellent material! There was one error in the last assignment that cost me a lot of time. Please fix that. Otherwise, very useful programming assignments.

교육 기관: SUNIL D

Jul 07, 2019

Very Good Course to understand Step by Step

Hyperparameter tuning, Regularization and Optimization to improve Deep Neuaral Networks & Practical Assignments !

교육 기관: Rekhawar N N

Dec 14, 2019

improving Deep Neural networks :Hyperparameter tuning,Regularization and optimization course was amazing! thank you so much coursera and Andrew Ng sir! :))

교육 기관: Alex C

Sep 24, 2017

Please offer a lecture note in detail instead of just ppt shows for each class video, not to mention that some are missing which is inconvenient to recap.

교육 기관: Muhammad B A

Jun 25, 2018

Great material and lectures. Would've preferred slightly more comprehensive exercises though, and more on tensorflow(any deep learning framework) as well

교육 기관: Francois-Xavier

Dec 18, 2017

The tensorflow programming assignment was a little too easy. It turned out to be more or less of a copy paste work without having to look at the TF docs.

교육 기관: Flaviu I V

Apr 07, 2018

I feel like the second course was better then the first one. But there are a couple of typos in some assignments and the assignments are still too easy.

교육 기관: Mark M

Oct 30, 2017

The intro of hyper parameters was from mathematical point of view as good as the basics of week 1, however practical relevance becomes not really clear.

교육 기관: Stephan W

Sep 02, 2017

As always - excellent lectures by Andrew Ng. However, I think that the programming assignments tend to be a it too easy and a bit too much "copy/paste".

교육 기관: Sergey

Oct 06, 2019

I wish prof. Ng provided more intuitions into underlying math particularly why gradient optimization techniques help. But like it anyways, very useful!