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Back to Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

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

4.9
stars
63,378 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 31, 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.

AS

Apr 19, 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

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6901 - 6925 of 7,273 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Agnes

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Oct 13, 2017

it is very useful for the processing of modelling.

By ZHE C

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Aug 18, 2017

include key idea on the tuning of hyperparameters

By Ahmed H

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Dec 20, 2022

multiclass classification need more illustration

By pranav b

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Jan 28, 2020

Best Course For Learning Hyper parameters Tuning

By 鞙る彊欷�

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Mar 8, 2019

REALLY USEFUL.

BUT IT IS BIT HARD FOR BEGINNERS.

By Sumitabha B

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Jun 10, 2022

The last tutorial on Tensorflow could be better

By Shoaib Z

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Dec 29, 2020

1st and 2nd weeks are still somewhat confusing.

By bahri d

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Nov 25, 2020

Teorik anlat谋m harika ama uygulama k谋sm谋 eksik.

By JEROME D

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Sep 16, 2020

More than 10 videos is too much for just 1 quiz

By Nims F

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Jun 19, 2020

amazing course with an amazing teaching method.

By Santosh P

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Mar 23, 2020

Excellent course. Bit tougher than first course

By Kousik R

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Jun 12, 2019

There are so many grader problems please fix it

By Abhijith A

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Oct 2, 2018

Good course, could have done more on tensorflow

By abiran r

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Jul 12, 2020

i learn a lot of things related to tensorflow

By Mike R

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Nov 2, 2019

Tensor flow should be explained in more detail

By Kullawat C

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Oct 2, 2018

Very great course on how to tune NN in details

By Harsha S

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Jan 23, 2018

Builds on fundamentals, which is always good!!

By Ti岷縩 H N

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Apr 6, 2021

The coding assignment is not challenge enough

By Paraskevas P

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Mar 30, 2020

More practical examples would be very useful.

By Aymen S

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Aug 13, 2019

Cours int茅ressant merci beaucoup Mr Andrew Ng

By Anna W

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Sep 12, 2018

batch optimization is good but not graded :-(

By Yiping W

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Jun 24, 2018

should provide more materials for tensor flow

By Abhishek A

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Nov 25, 2021

Tensor Flow could have been elaborated more.

By MD N F

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Feb 15, 2021

Concepts explanation was not up to the mark.

By Freddy A C F

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Jun 26, 2020

great now I understand Adam optimizer better