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

4.9
stars
62,864 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

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

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6876 - 6900 of 7,219 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By MD N F

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Feb 15, 2021

Concepts explanation was not up to the mark.

By Freddy A C F

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Jun 25, 2020

great now I understand Adam optimizer better

By Kazuki H

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Jan 9, 2020

I can understand concept of deep neural net!

By Bernardt D

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Jun 26, 2018

There were some typos throughout the course.

By Michael N

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Apr 13, 2018

Great but som explanations seems a bit wierd

By Karl B

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Oct 28, 2018

Tensor flow stuff could be better explained

By Mecrux

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Sep 4, 2018

Maybe should spend more time on tensorflow?

By Arnav D

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May 21, 2018

Best TensorFlow tutorial I have seen so far

By Sandor T C

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Jan 29, 2018

too much hand holding, no struggle to learn

By John R G P

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Aug 19, 2020

Its necessary to actualize to tensorflow 2

By Paulo A V

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Nov 16, 2017

Nice complement to the first course on ANN

By Lina H

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Aug 4, 2022

I wish it had moe practical assignments.

By thibault c

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Nov 7, 2019

more intuitive insights would be helpful

By EURICO O D C D S C

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Jan 8, 2018

Having tensorflow is great. It's a must.

By taofeek o

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Mar 12, 2020

A great course and it's well explained.

By Dex D X

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Oct 16, 2017

programming assignments are too easy XD

By John Y

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Sep 15, 2017

Programming assignments are too simple.

By Michael B

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Dec 19, 2017

Could do with more tensorflow examples

By Guy K

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Sep 22, 2017

Well organized !! clear explanations !

By Mayank J

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May 13, 2020

I expected it to be in TensorFlow 2.0

By jyning

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Dec 3, 2017

感觉作业设计的很好，可以不需要太好的编程能力就能完成，还能加深多算法的理解

By Y C

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Jan 10, 2021

tensor flow could be upgraded to 2.0

By Merouane B

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Jun 16, 2020

it was difficult somehow but awesome

By Yogesh K

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May 28, 2020

Update to TensorFlow 2.0 is required

By Krupal b

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May 24, 2020

Some model are not understood deeply