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Back to Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

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

4.9
stars
63,068 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

XG

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Thank you Andrew!! I know start to use Tensorflow, however, this tool is not well for a research goal. Maybe, pytorch could be considered in the future!! And let us know how to use pytorch in Windows.

YL

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very useful course, especially the last tensorflow assignment. the only reason i gave 4 stars is due to the lack of practice on batchnorm, which i believe is one of the most usefule techniques lately.

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4051 - 4075 of 7,239 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Ulas M C

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Dec 11, 2019

Easy to follow, great assignments.

By 홍진우

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Dec 1, 2019

좋았습니다. 많은 내용을 실무에 적용할 수 있을 것 같습니다!

By Jannah P

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Oct 28, 2019

just as great as the first course!

By Gustavo R L

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Sep 21, 2019

Very good explanation about tuning

By salim m

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Jul 19, 2019

Excellent, i like the assignments.

By 王明

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Jun 15, 2019

课程指导非常详细，尤其配合编程作业，原理与实践结合，非常透彻，喜欢！

By SW J

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Dec 21, 2018

It's very much helpful. Thank you.

By Yash H J

•

Dec 16, 2018

Improved by knowledge drastically!

By Thomas R

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Nov 3, 2018

Professor Andrew Ng, thanks a lot.

By Haitao C

•

Nov 1, 2018

Great course, clear, easy to learn

By Kedar D G

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Aug 28, 2018

awesome explaination by Sir Andrew

By Goodorc

•

Aug 6, 2018

Much harder than the first lesson.

By byehero

•

Jul 18, 2018

我非常喜欢这门课程，内容很详细，我能听懂，而且可以自己能实现一些应用

By leauyn

•

Jul 7, 2018

Great course, wonderful assignment

By Iraklis K

•

Jun 24, 2018

Great course! Very well organized!

By zhaochengshuai

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May 6, 2018

wonderful class, I reall enjoy it!

By Julio

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Mar 14, 2018

this course have interesting thing

By ESWAR L

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Feb 20, 2018

very concise lectures by Andrew NG

By Milos D

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Dec 31, 2017

Excellent as every one from Andrew

By Tony Z

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Dec 5, 2017

Excellent course in deep learning.

By Aaron W

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Oct 21, 2017

easy understandable, good teaching

By Jean M A S

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Oct 18, 2017

Very good, like the first course !

By Zhi-lin L

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Oct 8, 2017

Ng tell you how to nudge the model

By hangtian.jia

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Sep 30, 2017

Great! Very fundamental materials!

By Hussein M

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Sep 18, 2017

Great and very interesting course.