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

4.9
stars
63,489 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

NC

Aug 18, 2017

Yet another excellent course by Professor Ng! Really helped me gain a detailed understanding of optimization techniques such as RMSprop and Adam, as well as the inner workings of batch normalization.

BA

May 31, 2020

Very good course, useful and smart. Some of the example are on tensorflow 1 but I think that they will update them soon to keras tf2 Thank you!I will pass on what I have learned here to undergrads :)

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5976 - 6000 of 7,283 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By znyuan

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Aug 25, 2019

很实用哦

By Dipanjan C

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Jul 16, 2019

mice

By SiYingYao

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Apr 1, 2019

good

By 용석 권

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Mar 22, 2019

Good

By Shirish P

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Feb 12, 2019

Best

By Akash G

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Feb 5, 2019

good

By 朱柏霖

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Jan 23, 2019

nice

By xuezhibo

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Jan 20, 2019

nice

By ANKIT S

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Dec 16, 2018

Good

By Jhon S

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Nov 25, 2018

cool

By 夏天

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Nov 18, 2018

good

By hengfengtian@126.com

•

Nov 15, 2018

深入浅出

By 王志珍

•

Oct 10, 2018

超级棒！

By Thành N K

•

Oct 5, 2018

good

By Thái T

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Oct 3, 2018

good

By 徐玄清

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Aug 22, 2018

nice

By Vamsi K C

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Aug 19, 2018

Good

By Khoa V A

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Jul 29, 2018

good

By tiekun c

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Jul 26, 2018

nice

By 定之 胡

•

Jul 19, 2018

很好~~

By WD

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Jul 16, 2018

good

By 周树宇

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Jul 12, 2018

good

By Harsh D

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Jul 1, 2018

good

By Will R

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Jun 28, 2018

dope

By 王欢

•

Jun 6, 2018

Cool