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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

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63,492 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

AS

Apr 18, 2020

Very good course to give you deep insight about how to enhance your algorithm and neural network and improve its accuracy. Also teaches you Tensorflow. Highly recommend especially after the 1st course

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

筛选依据：

6926 - Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization 的 6950 个评论（共 7,283 个）

创建者 Tiến H N

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Apr 6, 2021

The coding assignment is not challenge enough

创建者 Paraskevas P

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Mar 29, 2020

More practical examples would be very useful.

创建者 Aymen S

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Aug 13, 2019

Cours intéressant merci beaucoup Mr Andrew Ng

创建者 Anna W

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Sep 12, 2018

batch optimization is good but not graded :-(

创建者 Yiping W

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Jun 23, 2018

should provide more materials for tensor flow

创建者 Abhishek A

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Nov 24, 2021

Tensor Flow could have been elaborated more.

创建者 MD N F

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Feb 15, 2021

Concepts explanation was not up to the mark.

创建者 Freddy A C F

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Jun 25, 2020

great now I understand Adam optimizer better

创建者 長谷川一輝

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Jan 8, 2020

I can understand concept of deep neural net!

创建者 Bernardt D

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Jun 26, 2018

There were some typos throughout the course.

创建者 Michael N

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Apr 13, 2018

Great but som explanations seems a bit wierd

创建者 Karl B

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Oct 28, 2018

Tensor flow stuff could be better explained

创建者 Mecrux

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Sep 4, 2018

Maybe should spend more time on tensorflow?

创建者 Arnav D

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May 21, 2018

Best TensorFlow tutorial I have seen so far

创建者 Sandor T C

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Jan 29, 2018

too much hand holding, no struggle to learn

创建者 John R G P

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Aug 19, 2020

Its necessary to actualize to tensorflow 2

创建者 Paulo A V

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Nov 16, 2017

Nice complement to the first course on ANN

创建者 Lina H

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Aug 4, 2022

I wish it had moe practical assignments.

创建者 thibault c

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Nov 7, 2019

more intuitive insights would be helpful

创建者 EURICO O D C D S C

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Jan 8, 2018

Having tensorflow is great. It's a must.

创建者 taofeek o

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Mar 12, 2020

A great course and it's well explained.

创建者 Dex D X

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Oct 16, 2017

programming assignments are too easy XD

创建者 John Y

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Sep 14, 2017

Programming assignments are too simple.

创建者 Michael B

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Dec 19, 2017

Could do with more tensorflow examples

创建者 Guy K

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Sep 21, 2017

Well organized !! clear explanations !