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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

RR

Jun 13, 2020

Could have increased assignments and some more indepth knowledge of tensorflow and proper installation way of tensorflow cause mine is showing error when iam trying to practice as shown in the video

NC

Jun 3, 2018

Just as great as the previous course. I feel like I have a much better chance at figuring out what to do to improve the performance of a neural network and TensorFlow makes much more sense to me now.

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4051 - 4075 of 7,283 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Hongjian H

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Dec 25, 2017

Very useful and excellent lectures!

By Radhakrishna J

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Dec 16, 2017

Best course to start Deep Learning.

By David H C

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Nov 23, 2017

Amazing Tips, Andrew Ng is the best

By William M

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Oct 1, 2017

Great followup to the first course!

By Deleted A

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Sep 23, 2017

Extremely useful, also challenging.

By Martin J

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Sep 7, 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 29, 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 7, 2020

Very helpful course. Thanks a lot!

By SANTAHANAMARI

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May 16, 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 29, 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 ???

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Dec 1, 2019

?????. ?? ??? ??? ??? ? ?? ? ????!

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 22, 2019

Very good explanation about tuning

By salim m

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Jul 20, 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！