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

4.9
stars
62,896 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

AB

Aug 26, 2021

Amazing course which focus on the theoretical part of parameters tuning, but it needs more explanation of Tensorflow, as I felt a little lost in the last project. Except that, it is an amazing course.

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3501 - 3525 of 7,219 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Ruben R R

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Aug 26, 2020

Lots of useful concepts, with hands-on examples!

By Glendon H

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Aug 12, 2020

Thanks Andrew! Your explanations are excellent!

By YounghaeKim

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Jul 25, 2020

Always Thanks to Andrew for high quality course.

By MANOJ K

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May 12, 2020

Great content for beginners and concept focused.

By Haoran L

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Mar 18, 2020

Very concise and informative. Loved the homework

By Carlos A J H

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Feb 7, 2020

Excelent course, as always with professor Andrew

By Mayank A

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Feb 4, 2020

Please provide slides at the end of whole course

By Claudio U R

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Sep 8, 2019

The course helps to implement neural-networks.

By Kseniia P

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Jun 30, 2019

Informative course with well-guided assignments.

By Nicolas D

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Mar 3, 2019

Very nice methodological lesson on deep learning

By Hichem M

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Dec 7, 2018

J'ai beaucoup apprécié ce cours !

it was great !

By narain p

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Nov 24, 2018

it was a very good content to start from scratch

By Ehsan G

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Oct 25, 2018

Last week was so fast, particularly tensor flow.

By Michele C

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Jul 19, 2018

useful, clear and exercises were not frustrating

By RODOLFO X B

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Apr 29, 2018

It is a great course, but you need the first one

By Arun

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Mar 6, 2018

Prof. Andrew Ng has done it again! Great course!

By 任宇凡

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Feb 28, 2018

excellent! Informative while easy to understand.

By Giulio T

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Dec 2, 2017

Great insights into the tuning of a Neaural Net!

By Rihab B A

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Nov 25, 2017

Great level of details again Andrew. Keep it up!

By Muhammed B

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Nov 11, 2017

This course is great for hyperparameter tuning .

By Jingbo L

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Oct 22, 2017

Very clear, and gives good points on the basics.

By Robin

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Sep 28, 2017

Nice course for good foundation in deep learning

By Truman P

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Sep 10, 2017

A detailed look into some really practical bits!

By Yongtao M

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Aug 25, 2017

It become more interesting than the first course

By Ernesto R M

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Oct 8, 2023

Excelente curso, buena relacion teoria practica