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返回到 Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

学生对 DeepLearning.AI 提供的 Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization 的评价和反馈

4.9
63,507 个评分

课程概述

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....

热门审阅

BA

May 31, 2020

Very good course, useful and smart. Some of the example are on tensorflow 1 but I think that they will update them soon to keras tf2 Thank you!I will pass on what I have learned here to undergrads :)

DH

Apr 26, 2020

Everything, Everyparameter in neural networks looks familiar to me now. I feel like I can optimize them for better accuracy. Overall I learned some new things and the way of teaching was really nice.

筛选依据:

3301 - Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization 的 3325 个评论(共 7,286 个)

创建者 Elvis K

Oct 15, 2017

Great example, let you easy to understand Deep learning

创建者 Victoria G

Sep 30, 2017

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

创建者 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。

创建者 Mustafa S

Sep 20, 2017

A good teacher with very clear explanations !! the best

创建者 Ling J

Sep 19, 2017

This is a very aggressive course in deep learning area.

创建者 Palathingal F

Sep 13, 2017

Attention to detailed explanations is much appreciated.

创建者 Hongbin G

Aug 24, 2017

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

创建者 Sushwet K P

Apr 16, 2022

Amazing, straightforward and to the point explanations

创建者 Daniel M d S

Mar 21, 2022

Curso de extrema qualidade, muito simples e aplicável.

创建者 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

创建者 YesMan F

Jul 29, 2021

a huge thanks to deeplearning ai for the great course

创建者 עידן ק

Jun 15, 2021

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

创建者 Vinh T

Jul 10, 2020

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

创建者 Arunabha D

Jul 6, 2020

Great materials and exercises,great teaching by Andrew

创建者 Yang X

Jun 23, 2020

Answered many of my doubts about deep neural networks!

创建者 Shailesh K

May 11, 2020

Simply awesome go for it. Thank you so much Andrew sir

创建者 Varun K

May 2, 2020

Great course! Love Andrew Sir's teaching. Keep it up!!

创建者 v. s k

Mar 31, 2020

great teaching in an easier approach. Thanks Andrew :)

创建者 Purod D

Feb 6, 2020

I learned a lot from this course. Thank you, Coursera.

创建者 신우석

Jan 15, 2020

모델의 결과를 어떻게 향상시킬 수 있는지 등 세세한 부분을 잘 가르쳐주십니다. 앤드류쌤 최곱니다!

创建者 Deleted A

Dec 30, 2019

It helped me to understand concepts of tuning in depth

创建者 Amin N s

Jun 30, 2019

Awesome course that makes deep learning more tangible.

创建者 Omar H E K

Jun 24, 2019

The topics were advanced and practical, I am impressed

创建者 Jun W

May 16, 2019

Great course about tuning parameters of deep learning!

创建者 wttc

Mar 12, 2019

very useful easy-understand and impressiving courses