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

4.9
stars
63,175 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

CM

Dec 23, 2017

Exceptional Course, the Hyper parameters explanations are excellent every tip and advice provided help me so much to build better models, I also really liked the introduction of Tensor Flow

Thanks.

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3251 - 3275 of 7,254 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By sagar s

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Mar 20, 2018

With Respect, what a clarity on explaining the concepts!

By Cristian R M

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Feb 20, 2018

Very good mathematics even for people from Chemistry :-)

By Julian R

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Jan 8, 2018

Great lecture videos and very well-designed assignments.

By Alexandru E

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Dec 31, 2017

Fantastic course as we've gotten used to from Andrew Ng!

By Felipe M

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Dec 11, 2017

Nice course too, in the end it speeds up a bit too much.

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 .