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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

51,066개의 평가
5,766개의 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 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.


Apr 19, 2020

Very good course to give you deep insight about how to enhance your algorithm and neural network and improve its accuracy. Also teaches you Tensorflow. Highly recommend especially after the 1st course

필터링 기준:

Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization의 5,706개 리뷰 중 5376~5400

교육 기관: Thomas J D

Nov 08, 2018

Little less well structured/organized than the first course..

교육 기관: Qu S

Oct 27, 2018


교육 기관: Anirudh

Jun 28, 2018

not very happy about tensor flow introduction. rest was great

교육 기관: Serdar K

Feb 01, 2018

This was helpful. I advise spending more time on tensorflow.

교육 기관: abhishek s

Jun 22, 2020

not exactly a basic level course, its an intermediate course


Oct 23, 2019

Good but need to improve number of examples about tensorflow

교육 기관: Mark

Oct 11, 2018

Good course but a bit more detailed explanations were needed


Sep 28, 2017

good but would have been great if tensorflow is covered more

교육 기관: Henry V

Sep 25, 2017

A very good introduction, but a bit basic for professionals.

교육 기관: Suyash A J

Jun 11, 2020

Very Good Course, best if include notes for quick revision.

교육 기관: Vishakha S

Feb 05, 2020

I think a short video on tensorflow might help the learners

교육 기관: Ernst H

Jul 07, 2019

Obvious problems. Lessons and quizzes need to be polished.

교육 기관: Nick R

Jan 07, 2018

Necessary background information and how-to for algorithms.

교육 기관: Aarsh T

Jun 16, 2020

Loved the course, content and assignments are really good.

교육 기관: Disheng M

Mar 26, 2020

Tensorflow is kind of outdated, hard to find documentation

교육 기관: 熊子量

Feb 10, 2020

Less theoretical but more practical than the first course!

교육 기관: Ashraf A

Oct 26, 2019

Very good course and a good introduction to the tensorflow

교육 기관: Yating G

Jul 14, 2019

The courses are vey well organized and easy to understand.

교육 기관: Khosro ( P

Mar 22, 2019

Great course but homework assignments are a bit confusing!

교육 기관: zhixing x

Sep 08, 2018

Some mistakes in the notes, but overall it's a good course

교육 기관: Timothy D

Oct 03, 2017

This was a great course. Batch Norm blew my mind. Thanks

교육 기관: Karthi C

Jun 26, 2018

Became hard core technical but that's what it mean to be.

교육 기관: ภาณุเทพ ท

Jun 26, 2018

So far so good, but why no batch norm in last assignment.

교육 기관: Luis M A

Apr 04, 2018

As the 1st course, really easy to follow and interesting!

교육 기관: Evaristo C

Sep 17, 2017

Something that you won't see in many other MOOCs, worthy!