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
63,489 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

NC

Aug 18, 2017

Yet another excellent course by Professor Ng! Really helped me gain a detailed understanding of optimization techniques such as RMSprop and Adam, as well as the inner workings of batch normalization.

BA

May 31, 2020

Very good course, useful and smart. Some of the example are on tensorflow 1 but I think that they will update them soon to keras tf2 Thank you!I will pass on what I have learned here to undergrads :)

Filter by:

4426 - 4450 of 7,283 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Charles X

•

Sep 22, 2017

intuitive: from why to how

By Tony Y

•

Aug 23, 2017

very good tuning approach.

By Phước T L

•

Oct 3, 2023

Perfect ,Course very good

By Ingmar H

•

Jun 30, 2022

please next level now :)

By Namrata S

•

Jan 1, 2022

Very well curated course.

By muhammed n p

•

Nov 17, 2021

informative and enganging

By Abhinav S

•

Aug 30, 2021

Highly knowlegable course

By Prajwal C R

•

Jan 14, 2021

Best course for beginners

By Egor P

•

Oct 5, 2020

hopefully for next course

By JUAN D S C

•

Sep 28, 2020

Great lessons. Thank you.

By H A H

•

Aug 30, 2020

the best course ever ....

By Christophe P

•

Jul 8, 2020

Very useful to tune in NN

By Mauricio M

•

Jun 28, 2020

You will learn TensorFlow

By Ben - C L Y

•

Jun 5, 2020

Concise and super useful!

By Murtaza V

•

Jan 28, 2020

Great Learning Experience

By Amlan S

•

Sep 18, 2019

very good course. 100/100

By Petteri T

•

Sep 17, 2019

Excellent course again :)

By Martin Z

•

Dec 30, 2018

Absolutely fantastic! :-)

By Renjie T

•

Nov 29, 2018

Great Course! Appreciate!

By Bo Y

•

Oct 30, 2018

Very useful and practical

By Radoslav D

•

Oct 17, 2018

Outstanding! Very useful!

By Ilias P

•

Sep 5, 2018

(^_^) (^_^) (^_^)

By Dequan E

•

Jul 14, 2018

very instructive material

By KUN Q

•

Jun 19, 2018

Absolutely useful course.

By Stephen B

•

Jun 10, 2018

Great intro to TensorFlow