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

4.9
stars
63,465 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

DD

Mar 29, 2020

I have done two courses under Andrew ng and I am grateful to Coursera for their highly optimised and easily learning course structure. It has greatly help me gain confidence in this field. Thank you.

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

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3276 - 3300 of 7,282 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

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 24, 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.

By Shriraj P S

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Jul 5, 2018

Defacto best course to really break into Deep Learning!

By oWen H

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Jun 20, 2018

Great Awesome course! Thanks for sharing the knowledge!

By Jason T

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May 23, 2018

Learning so much about how to optimize neural networks!

By Estapraq M K

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May 18, 2018

great projects, I appreciate it! and great information!

By 张明

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Apr 15, 2018

This class is amazing. Thanks for Deeplearning.ai Team.

By Yangfan X

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Mar 24, 2018

The horse in "The problem of local optima" made my day.

By Adrián R

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Nov 20, 2017

Fantastic! I really like the explanations and exercises

By Николай А

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Oct 22, 2017

Great course! Very intersting and simple to understand!

By Elvis K

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Oct 15, 2017

Great example, let you easy to understand Deep learning

By Victoria G

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Sep 30, 2017

Excelent course! Thank you Andrew Ng and coursera-team.