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:

4176 - 4200 of 7,249 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Bahalul K

•

Nov 8, 2019

it is very helpful to my career

By Habibur M

•

Nov 4, 2019

Easy to understand. Thank you..

By Brendan F

•

Sep 2, 2019

Great explanations and examples

By Harish M

•

Jun 8, 2019

Very good lectures by Andrew Ng

By 김화겸

•

Apr 27, 2019

Andrew ng.... i love so much...

By Andrew

•

Oct 30, 2018

非常感谢coursera提供这么好的课程，内容很详实，收获很大

By Bình B N

•

Sep 6, 2018

Very good tips. Clear advice :D

By Xuhaoshen

•

Jul 1, 2018

Very Useful Course in Practice!

By CK S (

•

Jun 17, 2018

可以很清楚地了解整個參數調整的涵義跟DL基礎理論與實務的銜接。

By YixiangWang

•

Jun 17, 2018

i learnt a lot from Ng. Thanks.

By yifan

•

Jun 11, 2018

Andrew is such a great teacher!

By Wenbo W

•

Jun 8, 2018

an useful course and thank you!

By 劉劍峰

•

Apr 1, 2018

This course helps me a lot. thx

By debneil r

•

Mar 17, 2018

Learning TensorFlow was great!!

By Harsh S

•

Mar 13, 2018

Great. I love you Andrew Ng Sir

By Han K

•

Jan 19, 2018

excellent and insightful course

By Dharmik g

•

Jan 4, 2018

Great Course and great learning

By lixu

•

Dec 24, 2017

nice course, very appreciate Ng

By 振荟 王

•

Oct 26, 2017

66666666666666666666666666

很值得学习

By Jerry Y

•

Oct 11, 2017

Very nice and efficient course.

By 侍啸

•

Oct 10, 2017

improve my deeplearning ability

By Netik A

•

Oct 10, 2017

great things were taught easily

By Arun K S

•

Oct 9, 2017

It was a awesome learn learning

By Jose P

•

Aug 21, 2017

Great instructor, great course.

By Amit K c

•

Oct 17, 2024

The best course you will find!