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

4.9
stars
63,156 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

AS

Apr 18, 2020

Very good course to give you deep insight about how to enhance your algorithm and neural network and improve its accuracy. Also teaches you Tensorflow. Highly recommend especially after the 1st course

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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6701 - 6725 of 7,249 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Kumar V

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Oct 15, 2017

Good course could have been better expected little more on Tensor flow exercise.

By C. G F

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Sep 30, 2017

Clear and simple introduction to the topics. Useful hints and 'takeaway lessons'

By Abidur R

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Jun 25, 2020

Should have some TensorFlow Tutorials. I have found it difficult to understand.

By xiao c

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Apr 12, 2020

Good content. But I found the pace a little slow , maybe just my impatience. :)

By David A H V

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Mar 15, 2020

Great insights, however the programming assignments came with some minor issues

By Nicolo d G

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Feb 17, 2019

A bit short and light to be a course on its own but still useful in the series.

By Adrianus B K

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Oct 7, 2018

This course is a bit harder than the first one although it is only three weeks.

By Aris P

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Nov 24, 2017

Useful material and good teacher but the grading system has some serious issues

By Marco v d L

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Nov 4, 2017

Video's: 5 star

Practice: 3 star (it will test your copy and past skills mostly)

By Han T L

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Mar 21, 2021

A bit less structured than the 1st course, but still excellent! Learned a lot!

By Biral K P

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Aug 17, 2020

A great course overall. Implementation in TensorFlow 2.0 would have been nice.

By Andrew P

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Oct 28, 2019

Wonderful course, would have liked another assignment working with TensorFlow.

By bayu a n

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May 4, 2019

Need more in-depth about parameter tuning, but it's a very good course overall

By Mohit k

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Jun 22, 2018

Thanks for such amazing course. Add little bit more on Tensorflow fundamentals

By Lucas O S

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Dec 11, 2017

Great course, still some issues in quizzes and autograder, and lack of support

By Vladislav Z

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Oct 8, 2017

Course it good, but IMHO to simple.

BTW I do not have real experience with NN.

By Haim K

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May 30, 2020

It would be beneficial to give more details on how tensorflow optimizers work

By Ankur D W

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May 9, 2020

This is an important course to go through for improving deep neural networks.

By Luis d l O

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Jan 15, 2020

Very nice one. Focus on practical aspects that are quite necessary to use NNs

By Hossein M A

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Sep 9, 2019

too complicated, many lessens in couple of short videos.

poor video transcript

By Arturo V

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May 29, 2019

Se podría mejorar mucho la redacción del libro del ejercicio de programación.

By Alexander

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Nov 21, 2018

more python / tensorflow, as well as data exploration and cleaning is welcome

By Jiri L

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Jan 3, 2021

Very good. The only downside is the reliance on an old version of Tensorflow

By Damien C

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Sep 8, 2017

Excellent on the basis. could cite frameworks like hyperopt, hyperas, etc...

By Luigi C

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Aug 29, 2017

There are still some minor typos to correct, but it's a great course anyway!