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

4.9
stars
63,477 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 22, 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

MD

May 5, 2018

Would have liked to see the math and more complete explanations for all the things that Prof. Ng glosses over by saying "you don't really need to understand XYZ". Even if this material was optional.

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5626 - 5650 of 7,283 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Deleted A

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Mar 31, 2019

Excellent

By Matthew J B

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Mar 29, 2019

Fantastic

By jinpengcheng

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Feb 18, 2019

excellent

By Yannik L

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Jan 9, 2019

Excellent

By 黄怡欣

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Dec 11, 2018

very good

By 韩颖君

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Nov 1, 2018

VERY GOOD

By 郑睿

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Oct 26, 2018

very well

By Pankaj P S

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Oct 6, 2018

Loved it!

By Jian H

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Oct 2, 2018

fantastic

By SHASHANK P

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Sep 23, 2018

EXCELLENT

By ignacio v

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Sep 14, 2018

Ng rocks!

By Ethan

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Sep 1, 2018

Great sir

By Al T

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Aug 30, 2018

Excellent

By Zheng Z

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Aug 25, 2018

Very good

By Thomas A

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Aug 17, 2018

excellent

By nish2288

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Jul 20, 2018

Awesome !

By Fran T

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Jul 9, 2018

Loved it!

By Rajdeep

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Jun 17, 2018

Thank you

By Mohammad H

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Jun 12, 2018

Practical

By Trevor J

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Jun 2, 2018

Excellent

By 刘诗晗

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May 23, 2018

very good

By Shujjat A

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May 8, 2018

Fantastic

By 尹子龙

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May 1, 2018

i like it

By Mohamed H Y

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Apr 28, 2018

very good