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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
63,380 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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3576 - 3600 of 7,273 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By zawar k

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Nov 5, 2017

it is a good course with good learning material

By Harish S

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Oct 30, 2017

This was very interesting and practical course.

By 戚跃宇

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Oct 26, 2017

I love this course ,and i love Andrew.thank you

By Joffre L V

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Oct 11, 2017

Thanks, ... another step given in ML

Joffre Luis

By 洪锋

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Sep 20, 2017

Learned to useDNN framework to solve problems！

By Ajinkya C

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Nov 12, 2023

One of the best source to learn deep learning.

By Saumya R S

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Mar 23, 2021

really good concept, helped me learn, worth it

By Ernesto G d l P

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Mar 12, 2021

Brilliant, nice flow of assignments and theory

By Chetraj P

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Oct 2, 2020

The best Deep Learning Course in the internet.

By Piyas C

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Aug 16, 2020

The lecture of Professor Andrew Ng is amazing.

By Kyaw T H

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Jul 12, 2020

Very Excellent Course for DeepLearning Learner

By Yi S

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Jul 12, 2020

The most wonderful course about deep learning.

By Yair Y P V

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Jul 10, 2020

Great introduction to deep learning frameworks

By Sujit M

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Jun 10, 2020

Felt little complex. But finally completed it.

By Aishik R

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May 27, 2020

Tensorflow part coulda been more comprehensive

By Prem M

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Mar 1, 2020

A great course that gives you valuable skills.

By Akil R

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Jan 28, 2020

Great, well organised, student-centred course.

By Frank S

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Nov 11, 2019

Excellent!! Lots of fun. Clear explanations.

By Md. S R

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Sep 8, 2019

The last assignment on tensorflow is amazing!!

By Mohit P

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Jul 7, 2019

Love the way course is arranged.Thank you Sir.

By Akshay H

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May 21, 2019

Great course. Thanks to the instructor and TAs

By Camilo G

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Mar 2, 2019

Great way to introduce topics in Deep Learning

By chanish a

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Jan 6, 2019

I never have enjoyed this much while studying.

By Gautam E

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Jul 1, 2018

Nice to see a numpy vs tensor flow comparison!

By 田玉文

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Apr 15, 2018

I really like the lecture and enjoy the study.