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

4.9
stars
63,243 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

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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5976 - 6000 of 7,261 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By 夏天

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Nov 18, 2018

good

By hengfengtian@126.com

•

Nov 15, 2018

深入浅出

By 王志珍

•

Oct 10, 2018

超级棒！

By Thành N K

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Oct 5, 2018

good

By Thái T

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Oct 3, 2018

good

By 徐玄清

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Aug 22, 2018

nice

By Vamsi K C

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Aug 19, 2018

Good

By Khoa V A

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Jul 29, 2018

good

By tiekun c

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Jul 26, 2018

nice

By 定之 胡

•

Jul 19, 2018

很好~~

By WD

•

Jul 16, 2018

good

By 周树宇

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Jul 12, 2018

good

By Harsh D

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Jul 1, 2018

good

By Will R

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Jun 28, 2018

dope

By 王欢

•

Jun 6, 2018

Cool

By Yash R

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Apr 12, 2018

mast

By Mayur V

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Apr 8, 2018

dope

By Lie C

•

Feb 28, 2018

nice

By 铜 高

•

Jan 24, 2018

Cool

By Hao H

•

Jan 7, 2018

nice

By Leo D

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Jan 6, 2018

good

By skyfacon

•

Dec 6, 2017

nice

By Duoxiao C

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Nov 16, 2017

good

By Seungsoo L

•

Nov 9, 2017

good

By 李少辉

•

Nov 2, 2017

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