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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
63,484 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 9, 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

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.

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3601 - 3625 of 7,283 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By chanish a

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Jan 6, 2019

I never have enjoyed this much while studying.

By Gautam E

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Jul 1, 2018

Nice to see a numpy vs tensor flow comparison!

By 田玉文

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Apr 15, 2018

I really like the lecture and enjoy the study.

By Phu N

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Feb 21, 2018

Really good overview of tuning neural networks

By Yaw O

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Nov 19, 2017

Wonderful!. Looking forward to the next course

By Jon H

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Nov 7, 2017

great stuff and explanations and exercises !!!

By 孔燕斌

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Oct 19, 2017

great class, make deep learning more practical

By Joel G

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Oct 2, 2017

Great pedagogy, making complexity look simple!

By Pengju W

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Sep 20, 2017

It is a perfect course, which is easy to learn

By RobinChan

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Sep 7, 2017

Very useful methods of deep learning practice.

By Dax J

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Aug 31, 2017

great course, best one of this specialization.

By Jochen R

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Aug 30, 2017

great course about optimization and tensorflow

By 郭鑫鹏

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Aug 21, 2017

profundity with an easy-to-understand approach

By James P

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Mar 14, 2024

Excellent content and delivery from Andrew Ng

By Tomohito S

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Aug 27, 2022

ハイパーパラメータの调整はまったくの手探りだったので、体系的な探り方を知って感激しました。

By Zijian H

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Dec 12, 2021

Intense but straightforward. I learned a lot!

By Md. A H

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Sep 5, 2020

This was a tough and enjoyable course for me.

By ??t ? T

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Sep 3, 2020

This course is better than what i really want

By Kai L

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Jul 16, 2020

A good course to learn hyperparameters tuning

By Saeed A

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Jul 9, 2020

This is a great course and designed carefully

By Babatunde O

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Jul 5, 2020

Interesting concept professionally delivered.

By Akanksha M

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Jun 7, 2020

Concepts were very well and clearly explained

By priyanka V

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May 11, 2020

Best course on tuning the network parameters.

By Volk U

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May 7, 2020

Great instructor and easy to follow lectures.

By Prashant J

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Apr 6, 2020

A great course full of tips to tune DL Model.