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

4.9
stars
63,496 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

AA

Oct 23, 2017

Assignment in week 2 could not tell the difference between 'a-=b' and 'a=a-b' and marked the former as incorrect even though they are the same and gave the same output. Other than that, a great course

RR

Jun 13, 2020

Could have increased assignments and some more indepth knowledge of tensorflow and proper installation way of tensorflow cause mine is showing error when iam trying to practice as shown in the video

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5901 - 5925 of 7,284 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By beihai Q

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Nov 12, 2018

Good!

By Vinita M

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Oct 26, 2018

Great

By Simon H

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Oct 7, 2018

Great

By shenzhonghua

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Sep 3, 2018

Great

By 노재화

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Sep 2, 2018

Good!

By He L

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Jul 7, 2018

cool!

By Ashish B

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Jun 25, 2018

great

By jiahaozhou

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Jun 12, 2018

grate

By sachin

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Jun 10, 2018

super

By blaster_fire

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May 24, 2018

Good！

By Du L

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Feb 24, 2018

Best!

By Won J

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Feb 19, 2018

Great

By benedikt h

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Feb 18, 2018

Great

By lalaqingla

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Feb 8, 2018

good!

By 冉祥映

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Feb 5, 2018

nice.

By Minsub W

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Feb 2, 2018

good!

By qingjunwu

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Dec 20, 2017

Good!

By Siddarth V

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Dec 12, 2017

Great

By iron

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Dec 7, 2017

great

By 董雪振

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Dec 3, 2017

Good!

By Hiep N V

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Nov 18, 2017

G

r

e

a

t

By 崔宁

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Nov 14, 2017

GREAT

By Jian X

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Oct 30, 2017

挺不错的。

By Yates Y

•

Oct 24, 2017

Nice！

By wangdawei

•

Oct 16, 2017

good.