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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
63,380 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 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

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.

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3751 - 3775 of 7,273 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Shazam

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Dec 15, 2019

Assignments could be made a little tougher

By Shah N K

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Jul 20, 2019

This Course as much practical as it can be

By Zhou D

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May 31, 2019

very practical course! I am very grateful!

By Sachin P B

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Mar 5, 2019

Found it so helpful! Truly among the best!

By Caroline C

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Jan 21, 2019

Great sequel to course 1 for AI beginners.

By Ricardo A

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Jan 5, 2019

Very practical tools to apply to training!

By yongping.li

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Oct 27, 2018

a very very great and amazing class for me

By Liu W

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Jul 29, 2018

very useful for improving deep NN accuracy

By 朱琪超

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Mar 27, 2018

it is amzing. I have learned a lot.Thank U

By 史小向

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Mar 9, 2018

A wonderful course ,I learn a lot from it!

By Saket C

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Jan 15, 2018

Awesome course! Lot of new things to study

By Nitin K

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Dec 21, 2017

Thanks Andrew Sir and team awesome course.

By Jessie C

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Oct 23, 2017

Very nice course, and I like it very much!

By Caleb J R T

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Oct 9, 2017

Best introduction to Tensorflow framework!

By Manish A

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Oct 7, 2017

Very very informative. Gr8 learning curve.

By monica

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Oct 5, 2017

I would like more practice with TensorFlow

By Soubhik P

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Sep 26, 2017

Very well designed course. Thanks you sir.

By 罗锟

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Sep 13, 2017

very cool ! l have learned a lot from it !

By Alexey K

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Sep 9, 2017

As usual, full of very lucid explanations.

By hadi n

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Jun 28, 2023

Great like all courses provided by Andrew

By BRABEEM S

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Jul 24, 2021

amazing

i hated the tensorflow part though

By Moiz A S

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Apr 9, 2021

Perfect and Detailed. Andrew is the best!

By Patrik O B

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Mar 24, 2021

Great course! I recommend it to everyone.

By AFEF B

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Nov 1, 2020

A great experience thank you Pr Andrew Ng

By Sanket B

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Aug 19, 2020

good takeaways for hyper-parameter search