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

4.9
stars
63,299 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

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.

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

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4051 - 4075 of 7,270 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By William M

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Sep 30, 2017

Great followup to the first course!

By Deleted A

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Sep 22, 2017

Extremely useful, also challenging.

By Martin J

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Sep 6, 2017

Great coverage of parameter tuning.

By Tom M

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Aug 25, 2017

Solid material for Deep Neural Nets

By Kaung H H

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May 23, 2022

Easy, Understandable explanations.

By Shreya S

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Sep 14, 2021

Amazing Content ! Very Insightful!

By Xixi Y

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Oct 28, 2020

excellent material and organiztion

By MoChuxian

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Sep 24, 2020

very nice course, thanks very much

By Ananya P

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Aug 31, 2020

great course!!! Thoroughly enjoyed

By Pranav M

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Jul 22, 2020

Best Course of the Specialization!

By Sreetama S

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Jun 6, 2020

Very helpful course. Thanks a lot!

By SANTAHANAMARI

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May 15, 2020

Very Clear presentation. Excellent

By Lester P

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Apr 20, 2020

Quedo muy satisfecho con el curso.

By Lam L

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Apr 17, 2020

Very detail and easy to understand

By Suraj V

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Feb 28, 2020

Very good course for deep learning

By Govind M

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Feb 11, 2020

lots of learning with key concepts

By Ulas M C

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Dec 12, 2019

Easy to follow, great assignments.

By 홍진우

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Dec 1, 2019

좋았습니다. 많은 내용을 실무에 적용할 수 있을 것 같습니다!

By Jannah P

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Oct 28, 2019

just as great as the first course!

By Gustavo R L

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Sep 21, 2019

Very good explanation about tuning

By salim m

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Jul 19, 2019

Excellent, i like the assignments.

By 王明

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Jun 15, 2019

课程指导非常详细，尤其配合编程作业，原理与实践结合，非常透彻，喜欢！

By SW J

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Dec 21, 2018

It's very much helpful. Thank you.

By Yash H J

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Dec 16, 2018

Improved by knowledge drastically!

By Thomas R

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Nov 3, 2018

Professor Andrew Ng, thanks a lot.