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Learner Reviews & Feedback for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization by DeepLearning.AI

4.9
stars
63,477 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

AA

Oct 22, 2017

Assignment in week 2 could not tell the difference between 'a-=b' and 'a=a-b' and marked the former as incorrect even though they are the same and gave the same output. Other than that, a great course

MD

May 5, 2018

Would have liked to see the math and more complete explanations for all the things that Prof. Ng glosses over by saying "you don't really need to understand XYZ". Even if this material was optional.

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5976 - 6000 of 7,283 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By znyuan

•

Aug 25, 2019

很实用哦

By Dipanjan C

•

Jul 16, 2019

mice

By SiYingYao

•

Apr 1, 2019

good

By 용석 권

•

Mar 22, 2019

Good

By Shirish P

•

Feb 12, 2019

Best

By Akash G

•

Feb 5, 2019

good

By 朱柏霖

•

Jan 23, 2019

nice

By xuezhibo

•

Jan 20, 2019

nice

By ANKIT S

•

Dec 16, 2018

Good

By Jhon S

•

Nov 25, 2018

cool

By 夏天

•

Nov 18, 2018

good

By hengfengtian@126.com

•

Nov 15, 2018

深入浅出

By 王志珍

•

Oct 10, 2018

超级棒！

By Nguyễn K T

•

Oct 5, 2018

good

By Thái T

•

Oct 3, 2018

good

By 徐玄清

•

Aug 22, 2018

nice

By Vamsi K C

•

Aug 19, 2018

Good

By Khoa V A

•

Jul 29, 2018

good

By tiekun c

•

Jul 26, 2018

nice

By 定之 胡

•

Jul 19, 2018

很好~~

By WD

•

Jul 16, 2018

good

By 周树宇

•

Jul 12, 2018

good

By Harsh D

•

Jul 1, 2018

good

By Will R

•

Jun 28, 2018

dope

By 王欢

•

Jun 6, 2018

Cool