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
63,283 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

Oct 31, 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.

AS

Apr 19, 2020

Very good course to give you deep insight about how to enhance your algorithm and neural network and improve its accuracy. Also teaches you Tensorflow. Highly recommend especially after the 1st course

Filter by:

7001 - 7025 of 7,269 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By 侯凌

•

Dec 2, 2017

Need slides and notes

By 石诚

•

Nov 21, 2017

week 3 has some typos

By Amardip G

•

Apr 22, 2019

Useful for Debugging

By Cosmin D

•

Oct 10, 2018

Good course overall!

By Onkar P

•

Dec 29, 2017

Another Great Course

By Eamonn G

•

Sep 4, 2019

Overall good class.

By Gerrit V

•

Aug 19, 2019

Sometimes quit slow

By Chin-Wei W

•

Aug 5, 2023

Can be more clear.

By Shukrullo N

•

Apr 12, 2021

Time well-spent ))

By Vaibhav v s

•

May 15, 2020

Awesome content...

By 배병선

•

Mar 25, 2020

Good for beginners

By akshay v

•

Jun 29, 2019

a little difficult

By shudhatma

•

Jun 17, 2018

A very good course

By CHANGHYUN A

•

Apr 1, 2021

excellent lecture

By Sonny M

•

Apr 20, 2020

Excellent course!

By Michael A

•

Mar 15, 2019

Add more quizzes.

By Fazni f

•

Sep 15, 2021

best course ever

By ARAVAPALLI P B V M

•

May 17, 2020

Excellent course

By Nono

•

Oct 31, 2019

Thank you,Andrew

By Frederick

•

Oct 6, 2018

very good course

By J C

•

Nov 20, 2017

Very Good Course

By Bala S

•

Aug 19, 2017

Fantastic course

By D A

•

Sep 26, 2020

it is very good

By Kim C

•

Sep 9, 2020

希望

æ›´æ–°

Tensorflow

2

By Oceanusity

•

May 11, 2019

pretty good one