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

4.9
stars
63,227 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

NA

Jan 13, 2020

After completion of this course I know which values to look at if my ML model is not performing up to the task. It is a detailed but not too complicated course to understand the parameters used by ML.

HD

Dec 5, 2019

I enjoyed it, it is really helpful, id like to have the oportunity to implement all these deeply in a real example.

the only thing i didn't have completely clear is the barch norm, it is so confuse

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5951 - 5975 of 7,258 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Amulya J

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May 6, 2020

good

By gangishetty m t

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Apr 21, 2020

good

By Steven

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Apr 12, 2020

good

By zhaoxinyang

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Mar 16, 2020

NIce

By garikipati v

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Feb 10, 2020

nice

By Tao N

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Feb 8, 2020

good

By do m T

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Jan 9, 2020

Good

By 黄卓恒

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Jan 6, 2020

Good

By VENKATESAN S

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Nov 7, 2019

good

By yinxiaobao

•

Oct 22, 2019

无可挑剔

By 魏英杰

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Sep 21, 2019

good

By Xiong Z

•

Sep 3, 2019

good

By znyuan

•

Aug 25, 2019

很实用哦

By Dipanjan C

•

Jul 16, 2019

mice

By SiYingYao

•

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

•

Jan 23, 2019

nice

By xuezhibo

•

Jan 20, 2019

nice

By ANKIT S

•

Dec 16, 2018

Good

By Jhon S

•

Nov 25, 2018

cool

By 夏天

•

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！