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
63,068 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

AA

Invalid date

Assignment in week 2 could not tell the difference between 'a-=b' and 'a=a-b' and marked the former as incorrect even though they are the same and gave the same output. Other than that, a great course

AM

Invalid date

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

Filter by:

3501 - 3525 of 7,244 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By preethi v

•

Nov 20, 2017

very useful course for tuning the neural network.

By Kalle H

•

Nov 9, 2017

Great course with clear well structured lectures.

By Jamie A M

•

Nov 5, 2017

By far one of the best uptodate courses about DL.

By Rishubh P

•

Nov 2, 2017

Awesome experience, learnt a lot from this course

By Lucas Y

•

Oct 29, 2017

A thorough course that progressed at an easy pace

By Nikola M

•

Oct 22, 2017

great course. Hope to see more of your good work.

By 刘宇轩

•

Oct 19, 2017

Not difficult to follow, while much to gain from.

By PRASHANT K R

•

Oct 12, 2017

Nothing could better than this...love this course

By Johnson N

•

Oct 11, 2017

wrong review oops. havent finished this class yet

By Jehwan K

•

Mar 18, 2024

it's a course to take many informational things.

By Xu Z

•

Nov 5, 2021

Deep into the Neural Networks with Professor Ng!

By Mantas B

•

Dec 30, 2020

Very straight forward and understanding course!

By Ruben R R

•

Aug 26, 2020

Lots of useful concepts, with hands-on examples!

By Glendon H

•

Aug 12, 2020

Thanks Andrew! Your explanations are excellent!

By YounghaeKim

•

Jul 25, 2020

Always Thanks to Andrew for high quality course.

By MANOJ K

•

May 12, 2020

Great content for beginners and concept focused.

By Haoran L

•

Mar 18, 2020

Very concise and informative. Loved the homework

By Carlos A J H

•

Feb 7, 2020

Excelent course, as always with professor Andrew

By Mayank A

•

Feb 4, 2020

Please provide slides at the end of whole course

By Claudio U R

•

Sep 8, 2019

The course helps to implement neural-networks.

By Kseniia P

•

Jun 30, 2019

Informative course with well-guided assignments.

By Nicolas D

•

Mar 3, 2019

Very nice methodological lesson on deep learning

By Hichem M

•

Dec 7, 2018

J'ai beaucoup apprécié ce cours !

it was great !

By narain p

•

Nov 24, 2018

it was a very good content to start from scratch

By Ehsan G

•

Oct 25, 2018

Last week was so fast, particularly tensor flow.