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Learner Reviews & Feedback for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization by DeepLearning.AI

4.9
stars
63,245 ratings

About the Course

In the second course of the Deep Learning Specialization, you will open the deep learning black box to understand the processes that drive performance and generate good results systematically. By the end, you will learn the best practices to train and develop test sets and analyze bias/variance for building deep learning applications; be able to use standard neural network techniques such as initialization, L2 and dropout regularization, hyperparameter tuning, batch normalization, and gradient checking; implement and apply a variety of optimization algorithms, such as mini-batch gradient descent, Momentum, RMSprop and Adam, and check for their convergence; and implement a neural network in TensorFlow. The Deep Learning Specialization is our foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI....

Top reviews

AM

Oct 8, 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

XG

Oct 30, 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.

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4801 - 4825 of 7,261 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By ashish j

•

Jun 11, 2019

Great Assignments

By supertian

•

Jun 3, 2019

It's very useful.

By Yongjian F

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May 25, 2019

Very interesting.

By Manish K

•

May 25, 2019

very good content

By zhou

•

Mar 31, 2019

非常详细，讲的特别好，还有实验课程

By James C

•

Feb 22, 2019

Very good course.

By JINWOO S

•

Feb 19, 2019

best course ever!

By AASHISH B

•

Feb 14, 2019

Awesome course :)

By HARENDRA S

•

Jan 3, 2019

Very good course.

By Eoghan T

•

Jan 1, 2019

Thanks, Prof. Ng!

By 朱荣鑫

•

Dec 22, 2018

As good as before

By Mohammed A B

•

Dec 15, 2018

awesome content !

By Motilal R S

•

Dec 3, 2018

Excellent Course!

By Stefan K

•

Nov 23, 2018

Very good course!

By 苏庆祝

•

Nov 22, 2018

very nice course.

By Bhaskar D

•

Nov 20, 2018

Excellent course!

By Shan-Jyun W

•

Nov 14, 2018

Love this course!

By Bogdan S

•

Nov 4, 2018

Excellent course!

By Zhidan W

•

Oct 17, 2018

Extremely helpful

By Jakub V

•

Sep 9, 2018

Depth and clarity

By Timur B

•

Sep 1, 2018

Excellent course!

By Vinay A

•

Aug 27, 2018

Fantastic Course.

By Deleted A

•

Aug 17, 2018

excellent courses

By Caique D S C

•

Jul 21, 2018

very good content

By Sicen D

•

Jun 5, 2018

Very Good Course!