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
63,156 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

NA

Jan 13, 2020

After completion of this course I know which values to look at if my ML model is not performing up to the task. It is a detailed but not too complicated course to understand the parameters used by ML.

HD

Dec 5, 2019

I enjoyed it, it is really helpful, id like to have the oportunity to implement all these deeply in a real example.

the only thing i didn't have completely clear is the barch norm, it is so confuse

Filter by:

5276 - 5300 of 7,249 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Pablo M P

•

Jul 28, 2019

Very useful!

By Đức T N

•

Jul 14, 2019

Super useful

By KALPAM S

•

Jul 13, 2019

great course

By Hang S

•

Jul 4, 2019

Good course!

By Timur B

•

Jul 1, 2019

Great class!

By Hins Y

•

Jun 29, 2019

Recommend!!!

By JIALIU Z

•

Jun 3, 2019

good course!

By Himanshu S

•

May 18, 2019

Great Course

By Illia K

•

May 17, 2019

very useful!

By 郑笙桦

•

Apr 14, 2019

Means a lot.

By Haoqiu W

•

Mar 31, 2019

nice teacher

By Anchal S

•

Mar 17, 2019

Geate Course

By Almir I

•

Mar 9, 2019

Great course

By 任华琛

•

Feb 1, 2019

very helpful

By Deleted A

•

Jan 27, 2019

Great course

By RAMA R R

•

Jan 27, 2019

Great Course

By Kaiqiang W

•

Jan 26, 2019

Pretty Good！

By Shravan M

•

Jan 17, 2019

Thank You!!!

By David

•

Jan 15, 2019

Very Useful!

By Lakshmi N S

•

Jan 14, 2019

Nice course.

By Ahmed D

•

Jan 13, 2019

very amusing

By Dhananjay O

•

Jan 8, 2019

great course

By To P H

•

Jan 1, 2019

Great course

By 洪天悦

•

Dec 24, 2018

Good content

By sag s

•

Dec 1, 2018

Just AWESOME