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

4.9
stars
63,243 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

AM

Oct 8, 2019

I really enjoyed this course. Many details are given here that are crucial to gain experience and tips on things that looks easy at first sight but are important for a faster ML project implementation

AB

Aug 26, 2021

Amazing course which focus on the theoretical part of parameters tuning, but it needs more explanation of Tensorflow, as I felt a little lost in the last project. Except that, it is an amazing course.

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5901 - 5925 of 7,261 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Won J

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Feb 19, 2018

Great

By benedikt h

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Feb 18, 2018

Great

By lalaqingla

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Feb 8, 2018

good!

By 冉祥映

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Feb 5, 2018

nice.

By Minsub W

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Feb 1, 2018

good!

By qingjunwu

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Dec 20, 2017

Good!

By Siddarth V

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Dec 11, 2017

Great

By iron

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Dec 7, 2017

great

By 董雪振

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Dec 3, 2017

Good!

By Hiep N V

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Nov 18, 2017

G

r

e

a

t

By 崔宁

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Nov 13, 2017

GREAT

By Jian X

•

Oct 30, 2017

挺不错的。

By Yates Y

•

Oct 24, 2017

Nice！

By wangdawei

•

Oct 15, 2017

good.

By 段立溟

•

Oct 14, 2017

表白吴伯伯

By Dave P

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Oct 10, 2017

Hello

By Shiyuan Z

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Oct 2, 2017

good!

By 刘其波

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Oct 2, 2017

good!

By Rafael L

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Sep 26, 2017

I

t

i

s

a

By Hong W

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Sep 24, 2017

Sweet

By Edisson R

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Aug 24, 2017

12/10

By Mohanraj S 2

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Jun 30, 2024

good

By 1544_OMM J

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Sep 18, 2023

good

By Kiệt H V T

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Apr 7, 2022

Nice

By 1172陳耑任

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Mar 10, 2022

good