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

4.9
stars
63,156 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

NA

Jan 13, 2020

After completion of this course I know which values to look at if my ML model is not performing up to the task. It is a detailed but not too complicated course to understand the parameters used by ML.

HD

Dec 5, 2019

I enjoyed it, it is really helpful, id like to have the oportunity to implement all these deeply in a real example.

the only thing i didn't have completely clear is the barch norm, it is so confuse

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4051 - 4075 of 7,249 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By SANTAHANAMARI

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May 15, 2020

Very Clear presentation. Excellent

By Lester P

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Apr 19, 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 11, 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.

By Haitao C

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Nov 1, 2018

Great course, clear, easy to learn

By Kedar D G

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Aug 28, 2018

awesome explaination by Sir Andrew

By Goodorc

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Aug 6, 2018

Much harder than the first lesson.

By byehero

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Jul 18, 2018

我非常喜欢这门课程，内容很详细，我能听懂，而且可以自己能实现一些应用

By leauyn

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Jul 7, 2018

Great course, wonderful assignment

By Iraklis K

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Jun 24, 2018

Great course! Very well organized!

By zhaochengshuai

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May 6, 2018

wonderful class, I reall enjoy it!

By Julio

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Mar 14, 2018

this course have interesting thing

By ESWAR L

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Feb 20, 2018

very concise lectures by Andrew NG

By Milos D

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Dec 31, 2017

Excellent as every one from Andrew

By Tony Z

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Dec 5, 2017

Excellent course in deep learning.