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

4.9
stars
63,245 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 8, 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 30, 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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3976 - 4000 of 7,261 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Aditya G

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May 31, 2019

In love with Andrew NG. Huge respect

By Mohab

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Apr 21, 2019

top of top courses in deep learning

By Santiago G

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Apr 6, 2019

Excellent! Great as I was expecting!

By Duy-Hung N

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Jan 4, 2019

Thank you Andrew Ng you are my idol.

By jia-you, C L

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Nov 2, 2018

Thanks for this class what I learned

By Samuel H

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Oct 28, 2018

Lots of very useful information here

By sumeet r

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Oct 12, 2018

Very informative and quintessential.

By Jeromenicholas

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Oct 2, 2018

Extremely useful.

Andrew is a genius.

By Michael P

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Sep 6, 2018

Good explanation of RMSprop and Adam

By Pierre F

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Jun 19, 2018

Complete and well explained. Thanks.

By isaac b

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Jun 8, 2018

Another great course from Andrew Ng!

By Nicholas K

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May 13, 2018

Good mix of theory and hand-holding!

By Trace L

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Feb 26, 2018

Another stellar course by Andrew Ng!

By Carlo C

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Jan 24, 2018

Super well done! Thanks! Very clear!

By Vipul P

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Jan 14, 2018

Thank you Andrew, very good material

By Arvind S

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Jan 2, 2018

Awesome and extremely useful course!

By Cong C

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Dec 28, 2017

Contents are almost state of the art

By Calvin L

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Dec 25, 2017

Programming exercises were too easy.

By Steven S

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Nov 24, 2017

Excellent course!! Very informative!

By Siddhesh

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Oct 27, 2017

This is gonna be useful for my paper

By liu c

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Oct 18, 2017

very good teacher, very good lecture

By Deniz K

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Oct 18, 2017

Superb course. I would recommend it!

By 冯巍

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Oct 8, 2017

Well organized materials, Thank you!

By Pedro A R

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Oct 1, 2017

Very good introduction to TensorFlow

By MOHAMMAD H B M T

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Oct 1, 2017

very good course. easy to understand