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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

40,776개의 평가
4,340개의 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


Dec 06, 2019

I enjoyed it, it is really helpful, id like to have the oportunity to implement all these deeply in a real example.\n\nthe only thing i didn't have completely clear is the barch norm, it is so confuse


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 4,270개 리뷰 중 4001~4025

교육 기관: Dixing X

Oct 16, 2017

programming assignments are too easy XD

교육 기관: Ugo N

Oct 10, 2017

It's okay. It's get a bit hairy with all the notation and varied intuition, but it follows suit and is not impossible to understand! Thank you Dr. Ng, I look forward to more.


교육 기관: Arnav D

May 22, 2018

Best TensorFlow tutorial I have seen so far

교육 기관: Stuart R

Mar 11, 2018

Good course. Minor errors/typos in presented videos.

교육 기관: Miaoyin W

Oct 02, 2017

Need some improvement! I think the course is a little bit rush, especially on the 3rd week. I really like the 'test' assignments, which helps me to clear out a lot of important concepts. But the programming assignments sometimes bothers me not in the way of programming, but in the way of

교육 기관: Ganesh M S

Mar 31, 2018

The quality of the information is awesome. There are some minor bugs in the assignment section. Even though you have submitted the right answer it shows that you have secured 0 marks in that section. Apart from evaluation bug this course it super knowledgable.

교육 기관: Maciej B

Aug 22, 2017

Course is very good especially when revealing "secrets" of various optimization techniques. Once again programming excercise is rather easy to pass as you are guided step by step so there is no space for serious mistakes. More "open" excercises/chalenges would be desirable

교육 기관: Charles S

Nov 24, 2017

This course was excellent, however the Tensor flow at the end feels a little bit like the ML field is quickly being overtaken by the frameworks, and the Tensor flow section is a little bit tacked onto this course, maybe in a hurry.

교육 기관: Siwei Y

Nov 20, 2017

极高水准的教学,然课程略短。 编程作业依然过于保姆化 ,简直就是直接喂到嘴边。这样反而起不到加深印象的效果 。

교육 기관: Muhammad W

May 12, 2018

few mistakes in course assignment but overall good course material

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: Hamza M K

Jun 26, 2018

This is another great introduction to Depp learning frameworks apart from all the neural network performance upgrading techniques taught. This is an excellent course for building a strong foundation of deep learning fundamentals

교육 기관: Michael B

Dec 19, 2017

Could do with more tensorflow examples

교육 기관: 侯凌

Dec 02, 2017

Need slides and notes

교육 기관: Markus B

Sep 07, 2017

Pro: The course content is well explained and the examples are usually understandable. There are some well explained programming exercises that allow you to get in touch with the "machine room".

Con: Not enough programming exercises to explain all concepts and also the programming exercises sometimes boil down to copy&pasting some code from the instructions. Furthermore, I would expect that this couse with "intermediate" difficulty would allow you to really write code from scratch at some point instead of filling in "Jupiter" notebooks.

교육 기관: shuieryin

Jan 24, 2018

not very like tensorflow...

교육 기관: Muiz V

Oct 18, 2017

Programming assignments could have been more challenging. Otherwise, the course instructor is pretty awesome!! Thank you Andrew Ng.

교육 기관: Alejandro R

Oct 26, 2017

I miss the end of video quizzes, but can't rate it lower than 4 because this course is excellent.

교육 기관: Hakob J

Oct 11, 2017

It is very helpful course both for theoretical and practical aspects of Hyperparameter tuning

교육 기관: Yue X

Sep 15, 2017

Programming assignments are too simple.

교육 기관: alex g

May 13, 2018

great course

교육 기관: Potnuru A

Jun 18, 2018

This course provides more tips and ideas toward deep learning and introduces tensorflow. Worth it.

교육 기관: Satya S

Mar 21, 2018

they should have given more lectures on tensor flow but still it is a nice course

교육 기관: Yide Z

Dec 13, 2017

good course but there are some small bugs in video and exercises.

교육 기관: Yuki K

May 22, 2018