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

4.9
stars
63,295 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 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

XG

Oct 30, 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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7201 - 7225 of 7,270 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By luca m

•

May 5, 2020

I would have loved to have a session on TF2

By Kenneth C V

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Aug 29, 2019

Course is a bit complex due to the subject

By Kartheek

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Feb 1, 2019

week 3 topics would have been a bit better

By Tushar B

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Jun 12, 2018

Assignments vs lecture, difference is huge

By Aashita G

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Jun 1, 2020

fast paced not enough emphasis on topics

By Amod J

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Mar 18, 2018

Want to download my own work but cannot.

By Rachana O

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Aug 17, 2020

Can be done in more interesting manner.

By Mark L

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Jul 16, 2020

great superficial intro to the content

By jerome c

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Oct 14, 2018

Need more training on Tensorflow, imho

By Juan J D

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Sep 11, 2017

tensorflow subject was to superficial

By Weeha G

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Jul 25, 2021

Assignment of week 3 is toooo brief.

By SATHVIK S

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Jul 26, 2020

Can dive deeper into the mathematics

By Trevor M

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Nov 23, 2020

good lectures terrible exercises

By Maisam S W

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Oct 4, 2017

I still find tensorflow hard.

By Andrey L

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Oct 1, 2017

week 2 was extremely boring

By Cheran V

•

May 9, 2020

Outdated with Tensorflow 1

By QUINTANA-AMATE, S

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Mar 11, 2018

Again, nice videos but not

By Matthew P

•

Sep 3, 2021

Focused a bit on minutia.

By Adam G

•

Jul 11, 2020

Multiple grading issues.

By Chaitanya M

•

Jul 1, 2020

could be more engaging

By José A G R

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May 23, 2023

Estoy muy emocionada

By Cory N

•

Jan 8, 2020

Update for TF2.0 :)

By Алексей А

•

Sep 7, 2017

Looks raw yet.

By Ilkhom

•

Mar 21, 2019

awful sound

By Akhilesh

•

Mar 14, 2018

enjoyed :)