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

4.9
stars
63,243 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

AB

Aug 26, 2021

Amazing course which focus on the theoretical part of parameters tuning, but it needs more explanation of Tensorflow, as I felt a little lost in the last project. Except that, it is an amazing course.

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5876 - 5900 of 7,261 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Saoudi H

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Dec 29, 2019

great

By 芃維 陳

•

Oct 20, 2019

Nice!

By Mohamed B

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Oct 1, 2019

great

By hitskyer

•

Sep 22, 2019

学到了很多

By GuyChriqui

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Jun 12, 2019

great

By Chenqingming

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Jun 7, 2019

great

By Wei L

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Mar 31, 2019

Great

By Jan N

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Mar 20, 2019

Great

By Xu Y

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Mar 11, 2019

great

By Gzq

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Mar 10, 2019

great

By Hernan R

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Mar 6, 2019

Good!

By Yuhao L

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Jan 12, 2019

good!

By hexinlin

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Nov 29, 2018

great

By 钟胜杰

•

Nov 18, 2018

good!

By beihai Q

•

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

•

Sep 2, 2018

Good!

By He L

•

Jul 7, 2018

cool!

By Ashish B

•

Jun 24, 2018

great

By jiahaozhou

•

Jun 11, 2018

grate

By sachin

•

Jun 9, 2018

super

By blaster_fire

•

May 24, 2018

Good！

By Du L

•

Feb 24, 2018

Best!