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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

XG

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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.

YL

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very useful course, especially the last tensorflow assignment. the only reason i gave 4 stars is due to the lack of practice on batchnorm, which i believe is one of the most usefule techniques lately.

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3251 - 3275 of 7,239 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Sergio D

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Dec 9, 2017

excellent course! thanks a lot for putting this together

By Thomas P

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Oct 2, 2017

Course introduces exactly what it says it will introduce

By Magesh R

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Oct 2, 2017

Could have had extra tensorflow programming assignments.

By Ariel H

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Sep 13, 2017

Excellent strategies to implement a ML project!!! Thanks

By manaranjan p

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Sep 5, 2017

Excellent! Now I understood most of the deeper concepts.

By M N

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Aug 21, 2017

Excellent course from the legend Andrew Ng and his team.

By 성정환

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Jan 9, 2022

One of the best deep learning lectures I've ever taken!

By Tim C

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Jun 2, 2021

The assignments are very helpful, but a bit too simple.

By Mahmoud H

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May 24, 2021

I really like this course. thank you for the good work.

By Shrirang D

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Feb 10, 2021

Great insights, In-depth explanation for every concept.

By Mohamed A M

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Aug 20, 2020

I was impressed by this course, it was very beneficial.

By Marmik M

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Jul 16, 2020

Awesome content and hands-on practice for the beginner.

By ritik k

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Jul 8, 2020

Hands down the best course available on Coursera for DL

By Amol J

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Apr 18, 2020

No one can teach machine learning better than Andrew NG

By Abhay G

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Jan 23, 2020

Provides a good understanding of hyper parameter tuning

By yongheng l

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Jan 9, 2020

Easy to understand. The practice is very well designed.

By Pakin P

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Nov 28, 2019

Why not we update programming assignment to tensorflow2

By abderrahim b

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Sep 23, 2019

in fact this is best course for DL , thank you coursera

By Dharmendra K

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Aug 15, 2019

I couldn't have asked for better than this explanation.

By diwanshu s

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Jun 14, 2019

it's very nice for those who has taken AI full course .

By Hiroyoshi O

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Jun 9, 2019

Very good course to study fundamentals of deep learning

By Sridhar N

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Jun 7, 2019

Practical aspect of the NN will help in implementation.

By Babu, C

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Jan 7, 2019

Excellent optimization techniques articulated very well

By Ming-Yao W

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Aug 24, 2018

Make principles more easier to comprehend and to apply.

By Anuj A

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Aug 11, 2018

Very nice and deep explanation of each and every topic.