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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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3476 - 3500 of 7,273 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Chao ( Z

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Jan 15, 2018

Helpful and time-saving to get hang of this stuff.

By JUNGHOON C

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Nov 20, 2017

Quite difficult session but very meaningful course

By Krzysztof R

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Nov 14, 2017

Excellent, practically oriented course. Thank you!

By AlfredO

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Oct 26, 2017

Very well presented and the assignments are great.

By Ariel S

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Oct 5, 2017

Excellent course! Thanks to instructors and staff!

By Arushi A

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Oct 3, 2017

The pace and content of the course is brilliant :)

By Prakash C C

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Sep 22, 2017

Worth Studying. Very useful for practical insights

By Yixing Z

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Sep 15, 2017

Thanks Andrew and your team, really help me a lot!

By Clément N

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Jul 16, 2023

Excellent course! Prof Ng, is such a good teacher

By W?odzimierz J

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Jun 9, 2021

Good course. Nice mix of knowledge and exercises.

By 胡泽天

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Nov 23, 2020

So glad I can learn so many frameworks operations

By Fuad A

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Oct 11, 2020

It's a pretty interesting and well taught course.

By VADDANAM G

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Sep 12, 2020

Very well - taught by Andrew, thank you coursera.

By Derek L

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May 6, 2020

Great course to learn optimization of ML models!!

By 翁浩瀚

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May 5, 2020

it is very nice for the beginners in deep learnig

By Navdeep S H

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Apr 29, 2020

This Course is very helpful in improving my model

By Reem

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Apr 25, 2020

Valuable tips and insights throughout the course.

By kArThIk T

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Apr 10, 2020

I Need to revisit to get some solid understanding

By MIGUEL A Z G

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Jan 22, 2020

Great course! I'm very happy with the methodology

By Abhinav M

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Sep 10, 2019

I was a very good experience learning this course

By Viona Q

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Aug 21, 2019

Great course. Machine learning concepts made easy

By Jay T

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Jul 22, 2019

Excellent Course to strengthen your core concepts

By Jamil H

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Jul 12, 2019

A very good course with implementation techniques

By Hao L

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Jun 8, 2019

Really helpful! Keep on with the next course now!

By Terry P

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Jan 25, 2019

Very good course and well timed with great ideas.