Chevron Left
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
63,245 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.

Filter by:

4251 - 4275 of 7,261 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Sanket D

•

Aug 9, 2020

Very Informative and Detailed

By Dawood I

•

Jun 3, 2020

Can`t get any better. Awesome

By Shashti K N M

•

May 30, 2020

This was an excellent course.

By Tariq M

•

May 17, 2020

Thank You to all team members

By Jaeyong J

•

May 9, 2020

Great lecture with exercises!

By Byambadorj M

•

May 6, 2020

a great course for beginners.

By Eleonora

•

Apr 18, 2020

Clear and practical, loved it

By Seongwuk, H

•

Apr 17, 2020

This is perfect class for me.

By Naveen S P

•

Mar 30, 2020

It's Excellent experience !!!

By ding x

•

Mar 10, 2020

Very good, I get much help!!!

By Ivan C

•

Nov 20, 2019

very informative and thorough

By NITIN S

•

Nov 17, 2019

the most important one of all

By Adrien B

•

Oct 9, 2019

Every thing is cristal clear!

By sourav b

•

Sep 25, 2019

Course Materials are awesome.

By Moaz M

•

Jun 24, 2019

Exceptionally awesome course!

By dhananjay v

•

May 3, 2019

Andrew Neg is a simple genius

By Yang G

•

Jul 24, 2018

Very useful for practitioners

By 李润华

•

Jul 5, 2018

good lessons, really like it!

By Matthew S

•

May 8, 2018

Very in depth. Perfect speed.

By Jiahao Z

•

Mar 30, 2018

Lab excersise really helpful!

By Mateo R O S

•

Feb 19, 2018

Andrew Ng is a great teacher!

By Adarsh K J

•

Jan 16, 2018

awesome course, learned a lot

By Desigan P

•

Dec 13, 2017

Excellent! Thank you Prof Ng.

By Vidur S

•

Dec 7, 2017

Really smooth and informative

By joao c

•

Nov 6, 2017

As good as expected. 5 stars!