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:

5426 - 5450 of 7,249 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By 徐洁

May 1, 2022

Thank you!

By liubingxin

Apr 16, 2022

very well!

By Zelin W

Jan 20, 2022

Thank you!

By Qi S

Jan 19, 2022

Thank you!

By Chen

Jan 8, 2022

Thank you!

By Xin Y

Jan 1, 2022

Thank you!

By Shaofei Q

Nov 29, 2021

Thank you!

By Yi C

Oct 23, 2021

Thank you!

By Quan Y

Oct 21, 2021

Thank you!

By Krzysztof R

Jul 10, 2021

Excellent!

By Roberto C L

Jun 29, 2021

Fantástico

By Karl G

Mar 1, 2021

Excellent!

By Oscar M

Jan 9, 2021

Excelente!

By Felipe M

Nov 29, 2020

Very Nice!

By Deepak C

Nov 11, 2020

A good one

By azhar s

Nov 7, 2020

fell happy

By Hamidreza G

Aug 13, 2020

so great:)

By Furkhat K

Aug 9, 2020

very good!

By Haohan Z

Jun 23, 2020

very good!

By Sarang P

Jun 16, 2020

Conceptual

By Christine C

Jun 8, 2020

fantastic!

By Laxmi P

May 19, 2020

thnaku sir

By VITTE

May 11, 2020

Excellent.

By Shauvik D

Apr 26, 2020

Excellent!

By CLAUDIO C D R

Apr 17, 2020

Fantastic!