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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
63,484 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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3801 - 3825 of 7,283 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By 李瑞平

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Dec 18, 2017

more deep program exercise will be better

By Juan P V H

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Nov 2, 2017

Excelent Course..!! Highly recommended..!

By Mangesh K

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Oct 28, 2017

The Tensorflow assignment was awesome !!!

By Satyajit P

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Sep 27, 2017

Important course in DEEP learning series.

By Songpeng Z

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Sep 10, 2017

Many great techniques in neutral network.

By Meysam M

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Aug 27, 2022

Awesome. Thanks for this helpful course.

By Md M H G

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Sep 16, 2021

Great course for CS background students.

By Vinayaka S

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Jun 25, 2021

Very in-depth teachings and informative.

By Ashwani g

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Apr 10, 2021

the best course to know basic to advance

By Rohan H J

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Mar 16, 2021

A very good course which helped me a lot

By Abhishek S

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Oct 19, 2020

Excellent course with a lot of insights.

By Jyotin P

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Jul 13, 2020

Concepts greatly explained, Thanks a lot

By ?rky V d L S

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Jul 7, 2020

This was a excellent course. I'm amazed!

By Ali B

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Jun 28, 2020

I wish one day I could work with Andrew!

By TULIP P

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May 29, 2020

This course is great!! Great instructor!

By K K J

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May 3, 2020

Excellent Course, really in depth review

By AKIFUMI A

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Apr 25, 2020

Thank you very much for so great course!

By Yuvraj S C

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Apr 14, 2020

the milestone beginning in the DL career

By Daniel Z

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Mar 29, 2020

Able to follow and understand root cause

By Ahmed R

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Feb 29, 2020

It's more than excellent, it's flawless!

By Ricardo S

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Nov 29, 2019

One of the best courses I've ever taken.

By Abhishek

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Jul 10, 2019

stupendofantabulousfantagoricallymagical

By Tarun M

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Apr 10, 2019

My experience was really really awesome.

By Yuan L

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Mar 5, 2019

very practical and well organised course

By dmitry p

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Jan 10, 2019

Good course, just jupyter notebook hangs