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

4.9
stars
63,231 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

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

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.

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5651 - 5675 of 7,260 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By chenchang

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Jan 13, 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

•

Dec 9, 2017

very good

By Jie Z

•

Dec 6, 2017

Excellent

By Ding, x

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Dec 2, 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

吴恩达男神男神男神

By hugo

•

Nov 9, 2017

wonderful

By Andrés R d V

•

Oct 31, 2017

Very good

By chun

•

Oct 25, 2017

very good

By Michel-Alexandre C

•

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

•

Oct 5, 2017

Excellent

By Denny M

•

Sep 24, 2017

Nice! :-)

By LI S

•

Sep 19, 2017

very good

By 霍宇琦

•

Sep 18, 2017

thank you

By Hugsy W

•

Sep 17, 2017

very good

By Santosh P

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Sep 17, 2017

Wonderful

By Yanqing Y

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Sep 13, 2017

very good

By Arturas N

•

Sep 8, 2017

Good info