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

4.9
stars
63,169 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

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.

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

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6676 - 6700 of 7,253 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Deleted A

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Apr 17, 2020

Missing the notes in between the videos like in the Intro to Machine Learning course

By yesid a c m

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Oct 27, 2019

hay funciones de tensorflow que ser[ia adecuado que las explicaran en los notebooks.

By Asutosh S

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Jun 12, 2018

Assignments are too easy. They wouldn't even require one to watch the course videos.

By Samit H

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Jul 14, 2020

Very Good for knowing details . Few more practices in programming might help a lot.

By Cat-zilla

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Jan 13, 2020

4 stars for the course's rich content. minus one for the overly structured projects

By Andreas B O

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Jan 7, 2020

Excellent course - However, the Tensorflow tutorial could be a little more thorough

By emmanuel m

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Jan 31, 2021

Wish there was another weeks' worth of learning on tensorflow or more labs for it;

By Gil K

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Apr 14, 2020

A lot of good topics, but a lot of tasks are irrelevant for todays practical world

By VONGKASEM L

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Oct 19, 2018

some video lectures have some audio clips repeated, often at the end of the video.

By Bryan L

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Apr 8, 2018

Good explanation of gradient descent w/ momentum. Nice introduction to TensorFlow.

By V S P K

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Oct 6, 2017

Course content is intense. May be need more detailed videos/lecture on Tensor flow

By Domagoj

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Dec 11, 2021

Some exercises are not clear enough, that is why 4 stars, overall it is 5 stars.

By Ariel B

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Dec 16, 2020

Tensorflow 1 assignment should be updated to version 2

Otherwise very good course.

By Krishna T

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May 11, 2020

Loved the way how Prof.Andrew Ng explained everything in such a simplified manner

By Harsh B K

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Jul 29, 2019

Good Insights of hyper parameters with other techniques to improve learning rate.

By JETTIBOINA V N D S R P

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Jul 4, 2019

Content was excellent and it was delivered by Andrew Ng sir in an outstanding way

By Neeraj T

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Dec 27, 2018

I thoroughly enjoyed this course. Presents the material in an easy to learn style

By satyasai n

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Mar 20, 2018

they should have given more lectures on tensor flow but still it is a nice course

By mike b

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Jan 15, 2021

The assignment teaches tensorflow v1 where I would have expected v2, Keras, etc.

By Bezzecchi E

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Jan 7, 2021

Good understaning on why certains 'tricks' in nn tuning and regularization work.

By Marwan S

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Sep 10, 2020

In my opinion,the tensorflow framework should have been set in a separate course

By Martin B

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Aug 28, 2020

very good but TensorFlow requires more explanations especially in the last block

By Luis E G A

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Nov 23, 2019

great course, last videos (except for frameworks ) were somewhat hard to follow.

By Ran S

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May 17, 2019

More excersies on batch norm and hyper parameter search could have been usefull

By 成萧何

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Mar 26, 2019

A programming assignment about batch normalization and softmax will be helpful.