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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
63,493 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

AA

Oct 22, 2017

Assignment in week 2 could not tell the difference between 'a-=b' and 'a=a-b' and marked the former as incorrect even though they are the same and gave the same output. Other than that, a great course

AM

Oct 8, 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

筛选依据:

3276 - Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization 的 3300 个评论(共 7,283 个)

创建者 Mohamed A M

Aug 20, 2020

I was impressed by this course, it was very beneficial.

创建者 Marmik M

Jul 16, 2020

Awesome content and hands-on practice for the beginner.

创建者 ritik k

Jul 8, 2020

Hands down the best course available on Coursera for DL

创建者 Amol J

Apr 17, 2020

No one can teach machine learning better than Andrew NG

创建者 Abhay G

Jan 23, 2020

Provides a good understanding of hyper parameter tuning

创建者 yongheng l

Jan 9, 2020

Easy to understand. The practice is very well designed.

创建者 Pakin P

Nov 27, 2019

Why not we update programming assignment to tensorflow2

创建者 abderrahim b

Sep 23, 2019

in fact this is best course for DL , thank you coursera

创建者 Dharmendra K

Aug 15, 2019

I couldn't have asked for better than this explanation.

创建者 diwanshu s

Jun 14, 2019

it's very nice for those who has taken AI full course .

创建者 Hiroyoshi O

Jun 9, 2019

Very good course to study fundamentals of deep learning

创建者 Sridhar N

Jun 7, 2019

Practical aspect of the NN will help in implementation.

创建者 Babu, C

Jan 7, 2019

Excellent optimization techniques articulated very well

创建者 Ming-Yao W

Aug 24, 2018

Make principles more easier to comprehend and to apply.

创建者 Anuj A

Aug 10, 2018

Very nice and deep explanation of each and every topic.

创建者 Shriraj P S

Jul 5, 2018

Defacto best course to really break into Deep Learning!

创建者 oWen H

Jun 19, 2018

Great Awesome course! Thanks for sharing the knowledge!

创建者 Jason T

May 23, 2018

Learning so much about how to optimize neural networks!

创建者 Estapraq M K

May 18, 2018

great projects, I appreciate it! and great information!

创建者 张明

Apr 14, 2018

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

创建者 Yangfan X

Mar 24, 2018

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

创建者 Adrián R

Nov 20, 2017

Fantastic! I really like the explanations and exercises

创建者 Николай А

Oct 21, 2017

Great course! Very intersting and simple to understand!

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.