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

4.9
stars
63,068 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

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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

AM

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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

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3576 - 3600 of 7,244 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Kyaw T H

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Jul 12, 2020

Very Excellent Course for DeepLearning Learner

By Yi S

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Jul 11, 2020

The most wonderful course about deep learning.

By Yair Y P V

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Jul 9, 2020

Great introduction to deep learning frameworks

By Sujit M

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Jun 10, 2020

Felt little complex. But finally completed it.

By Aishik R

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May 27, 2020

Tensorflow part coulda been more comprehensive

By Prem M

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Mar 1, 2020

A great course that gives you valuable skills.

By Akil R

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Jan 28, 2020

Great, well organised, student-centred course.

By Frank S

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Nov 10, 2019

Excellent!! Lots of fun. Clear explanations.

By Md. S R

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Sep 7, 2019

The last assignment on tensorflow is amazing!!

By Mohit P

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Jul 7, 2019

Love the way course is arranged.Thank you Sir.

By Akshay H

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May 21, 2019

Great course. Thanks to the instructor and TAs

By Camilo G

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Mar 2, 2019

Great way to introduce topics in Deep Learning

By chanish a

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Jan 5, 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 14, 2018

I really like the lecture and enjoy the study.

By Phu N

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Feb 20, 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 6, 2017

great stuff and explanations and exercises !!!

By 孔燕斌

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Oct 18, 2017

great class, make deep learning more practical

By Joel G

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Oct 1, 2017

Great pedagogy, making complexity look simple!

By Pengju W

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Sep 19, 2017

It is a perfect course, which is easy to learn

By RobinChan

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Sep 6, 2017

Very useful methods of deep learning practice.

By Dax J

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Aug 30, 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