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

4.9
stars
63,157 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

CM

Dec 23, 2017

Exceptional Course, the Hyper parameters explanations are excellent every tip and advice provided help me so much to build better models, I also really liked the introduction of Tensor Flow

Thanks.

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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3276 - 3300 of 7,249 Reviews for Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

By Babu, C

Jan 7, 2019

Excellent optimization techniques articulated very well

By Ming-Yao W

Aug 24, 2018

Make principles more easier to comprehend and to apply.

By Anuj A

Aug 11, 2018

Very nice and deep explanation of each and every topic.

By Shriraj P S

Jul 5, 2018

Defacto best course to really break into Deep Learning!

By oWen H

Jun 19, 2018

Great Awesome course! Thanks for sharing the knowledge!

By Jason T

May 23, 2018

Learning so much about how to optimize neural networks!

By Estapraq M K

May 18, 2018

great projects, I appreciate it! and great information!

By 张明

Apr 15, 2018

This class is amazing. Thanks for Deeplearning.ai Team.

By Yangfan X

Mar 24, 2018

The horse in "The problem of local optima" made my day.

By Adrián R

Nov 20, 2017

Fantastic! I really like the explanations and exercises

By Николай А

Oct 21, 2017

Great course! Very intersting and simple to understand!

By Elvis K

Oct 15, 2017

Great example, let you easy to understand Deep learning

By Victoria G

Sep 30, 2017

Excelent course! Thank you Andrew Ng and coursera-team.

By 刘晓鹏

Sep 30, 2017

第一门课把深度学习的原理全面的讲解了一遍,而这门课,对超参数的调优作了系统性的讲解,在实际操作时知道从何入手。

By Mustafa S

Sep 20, 2017

A good teacher with very clear explanations !! the best

By Ling J

Sep 20, 2017

This is a very aggressive course in deep learning area.

By Palathingal F

Sep 14, 2017

Attention to detailed explanations is much appreciated.

By Hongbin G

Aug 24, 2017

Very good and helpful. The class is easy to understand.

By Sushwet K P

Apr 17, 2022

Amazing, straightforward and to the point explanations

By Daniel M d S

Mar 21, 2022

Curso de extrema qualidade, muito simples e aplicável.

By LTX

Sep 8, 2021

建议把第三周编程作业中的cost计算部分再优化一下不看论坛根本不知道还得把from_logits改成true

By YesMan F

Jul 29, 2021

a huge thanks to deeplearning ai for the great course

By עידן ק

Jun 15, 2021

you must to have must to learn and need for yourself!!

By Vinh T

Jul 10, 2020

Thankyou very much. This course is very useful for me!

By Arunabha D

Jul 6, 2020

Great materials and exercises,great teaching by Andrew