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Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization に戻る による Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization の受講者のレビューおよびフィードバック



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....



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.


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.


Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization: 4551 - 4575 / 4,786 レビュー

by Brent D

Feb 26, 2019

Tensorflow project was rushed and hard to understand.

by Franklin W

Jul 14, 2018

I want to be challenged more, less tips and more DIY.

by Seth T

Mar 26, 2018

Short course but was really excited to delve into TF.

by 王婷

Feb 17, 2018

good PA examples, that could benefit my further study

by Arhan G

Jan 31, 2018

Andrew is a great lecturer. The videos are excellent.

by Hak K C

Apr 05, 2018

Course was concise and assignments were well guided.

by Stuart R

Mar 11, 2018

Good course. Minor errors/typos in presented videos.

by Venkatraman

Mar 10, 2018

Quite not challenging in the programming assignments

by Fangshi L

May 19, 2019

Good course, although some bugs in homework grading

by Sumeet R

Feb 10, 2019

very good course - gets to practical aspects of ML!

by Juan O

Dec 03, 2017

Having slides like in other courses will be helpful


Dec 24, 2019

There should have been more exercise on tensorflow

by Gopal M

Sep 14, 2019

TensorFlow is a bit nebulous.I need more practice.

by Jean-Marc S

Dec 27, 2018

The syntax and logic of tensorflow is a bit blurry

by Daniel F P R

Dec 17, 2018

Was great! Would have loved to see more tensorflow

by 김연희

Dec 11, 2018

좋은 강좌입니다. 단 한글 번역 부분에 오류가 많습니다. 이후에는 수정되었으면 좋겠습니다.

by Shaun M

Jul 08, 2018

Good follow-on from course 1 of the specialization

by Mohammad M R

Jan 03, 2018

Sorry for the last review - the quiz can be saved.

by Gopala V

Oct 24, 2017

Definitely improved my understanding on the tuning

by erhan b

Oct 21, 2017

Assignments are mostly copy past from instructions

by Agnes

Oct 13, 2017

it is very useful for the processing of modelling.

by ZHE C

Aug 18, 2017

include key idea on the tuning of hyperparameters

by pranav b

Jan 28, 2020

Best Course For Learning Hyper parameters Tuning

by 윤동준

Mar 07, 2019



by santosh

Mar 22, 2020

Excellent course. Bit tougher than first course