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

4.9
stars
63,296 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

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5651 - 5675 of 7,270 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By kms g

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Mar 4, 2018

awesome!!

By Yash R S

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Feb 25, 2018

Excellent

By Eugene W

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Feb 23, 2018

Excellent

By jinil c

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Jan 28, 2018

Excellent

By Taekyung H

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Jan 21, 2018

Thank you

By saukhin s

•

Jan 19, 2018

top class

By chenchang

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Jan 14, 2018

very Good

By Nandigama V

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Jan 2, 2018

Excellent

By omar v

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Dec 24, 2017

Excellent

By 王琳娜

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Dec 17, 2017

very good

By 龙宪磊

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Dec 9, 2017

very good

By Jie Z

•

Dec 6, 2017

Excellent

By Ding, x

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Dec 3, 2017

excellent

By P S P R

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Dec 2, 2017

very good

By 姚朴健

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Nov 27, 2017

very good

By SAKURA

•

Nov 19, 2017

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By hugo

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Nov 9, 2017

wonderful

By Andrés R d V

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Nov 1, 2017

Very good

By chun

•

Oct 25, 2017

very good

By Michel-Alexandre C

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Oct 24, 2017

Excellent

By 陈尚伟

•

Oct 9, 2017

Ng出品，必属精品

By 超 宋

•

Oct 8, 2017

very nice

By password

•

Oct 5, 2017

very good

By Sylvain D

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Oct 5, 2017

Excellent

By Denny M

•

Sep 24, 2017

Nice! :-)