Chevron Left
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

52,522개의 평가
5,940개의 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 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.


Jan 14, 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.

필터링 기준:

Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization의 5,873개 리뷰 중 5351~5375

교육 기관: Matías L M

Oct 30, 2017

The professor is really good at explaining. The projects got more interesting than in the first course.

교육 기관: Per K

Oct 03, 2017

Get you to a more practical understanding of deep learning. The introduction to TensorFlow is valuable.

교육 기관: Alexandros I T

Mar 09, 2020

I would like to learn the V2 of TensorFlow. Except that. exceptional course. I love Andrew's teaching!

교육 기관: LEO L

Jul 31, 2019

All is good except the submission part, sometime return submission failure without specifying a reason

교육 기관: Hamza E B

Jun 22, 2019

Great Course ! I learned a lot, but I would have preferred another Framework though (like Pytorch) ...

교육 기관: Qingyun W

Jun 06, 2019

Some typos in the programming assignment is still not fixed (Mentioned in top posts in the discussion)

교육 기관: ryan m

Oct 08, 2018

a very informative course, I was introduced to Tensorflow through this course... I absolutely loved it

교육 기관: Dan C

Feb 28, 2018

I had a bug in my compute_cost function that caused cost to spiral but the grader did not catch it....

교육 기관: Yash J

May 18, 2020

There should have been deeper explanation for the tensor flow section. Otherwise an excellent course.

교육 기관: John C

May 18, 2020

Great instruction on the fundamentals. Probably need to update to Tensorflow 2 or just teach Keras.

교육 기관: Akshat D

Apr 22, 2020

This was one of the amazing courses I've ever attended on Coursera. Kudos to Andrew NG and the team.

교육 기관: sahil a

Mar 11, 2020

week 3 : Tensorflow framework explanation can be much better otherwise the whole course is very good

교육 기관: Lin Z

Mar 28, 2019

interesting introduction about deep neuro networks with examples on how to use Tensorflow framework.

교육 기관: Marijan S

Sep 09, 2018

I learned very useful info, but the last programming asignment with tensorflow was a pain in the a**

교육 기관: Gopal V K

Jul 15, 2020

A lot things I got to learn.Also the worksheet were properly designed to clear any doubt if one had

교육 기관: Apoorv A

Feb 04, 2019

I think things could have been more difficult. Currently it is way to easy to pass the assignments.

교육 기관: Potnuru A

Jun 18, 2018

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

교육 기관: Faniry R

Mar 14, 2018

Best explanation ever! Exercises should be made available even without a possibility of submission

교육 기관: Tirumala R M

Jan 24, 2018

Well explained the need of regularizations. Also python was best language to get assignments done.

교육 기관: Siddhi V T

Sep 19, 2019

An awesome course for someone who wants to learn how to tune the hyperparameters of their models.

교육 기관: Alexey V

Mar 18, 2019

Ran into bugs with some assignments, for example week 7 was not correctly calculating final model

교육 기관: Tamás J

Jun 14, 2018

Jupiter Notebook fails too offen! I had to close the window, start again, which is very annoying!

교육 기관: Chen X

Mar 27, 2018

It's fun they assume you know human error rate or optimal Bayesian. It's very rare in real world.

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: Prasad D D

Jul 02, 2020

Some examples to be solved manually would have helped get a better understanding of the concepts