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

4.9
stars
63,370 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

XG

Oct 30, 2017

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.

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4526 - 4550 of 7,272 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By bhawana

•

Aug 7, 2018

very informative course

By Line C

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Jul 10, 2018

Well structured course!

By Samuel N

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Jun 11, 2018

Good for understanding!

By BenjPau

•

Jun 9, 2018

i gained a lot. thanks.

By Sunghwan B

•

May 28, 2018

Thanks for this course!

By G C

•

Mar 24, 2018

Interesting and useful.

By Farhad D

•

Mar 20, 2018

It's completely useful.

By Tulsi J

•

Mar 14, 2018

This course is awesome.

By 吴鹏

•

Mar 13, 2018

Thank you,Learned a lot

By Arash A

•

Jan 16, 2018

Useful and informative.

By 伍平伟

•

Dec 1, 2017

课程引导很容易让人接受，建议有课程要点总结文档

By DayDayUp

•

Nov 28, 2017

harder than first class

By blaze s

•

Nov 22, 2017

nice course,learn a lot

By Guillermo C

•

Oct 30, 2017

Thorough and achievable

By Alan L

•

Oct 25, 2017

project seems too easy.

By Jiten R

•

Oct 8, 2017

Very informative course

By Harvey D

•

Oct 4, 2017

very clear and advanced

By Ola A

•

Sep 24, 2017

Very useful information

By Serdar B

•

Sep 23, 2017

Very informative course

By 张宇旻

•

Sep 9, 2017

浅显易懂，通过课程对超参优化等有了深入的理解。

By Ali A

•

Apr 4, 2022

very practical course.

By huy h

•

Sep 19, 2021

Thanks for this course

By Aakash R

•

Jul 29, 2021

Great course, loved it

By Nguyễn H V

•

Feb 1, 2021

Thanks to Mr Andrew Ng

By Alper D

•

Oct 27, 2020

Thanks for everything!