Chevron Left
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
星
63,489 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

DD

Mar 28, 2020

I have done two courses under Andrew ng and I am grateful to Coursera for their highly optimised and easily learning course structure. It has greatly help me gain confidence in this field. Thank you.

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：

6951 - Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization 的 6975 个评论（共 7,283 个）

创建者 Mayank J

•

May 13, 2020

I expected it to be in TensorFlow 2.0

创建者 jyning

•

Dec 3, 2017

感觉作业设计的很好，可以不需要太好的编程能力就能完成，还能加深多算法的理解

创建者 Y C

•

Jan 10, 2021

tensor flow could be upgraded to 2.0

创建者 Merouane B

•

Jun 16, 2020

it was difficult somehow but awesome

创建者 Yogesh K

•

May 28, 2020

Update to TensorFlow 2.0 is required

创建者 Krupal b

•

May 24, 2020

Some model are not understood deeply

创建者 Gerald B

•

Feb 14, 2018

Consistently challenging. I love it!

创建者 Abhay V

•

Mar 26, 2022

tought at times. but great overall.

创建者 Hans N

•

Apr 4, 2020

suggest to update to tensorflow 2.0

创建者 Sajal J

•

Oct 28, 2019

Very good course.highly recommended

创建者 Teodor C

•

Feb 13, 2021

tensorflow1 instead of tensorflow2

创建者 Shiva K

•

Aug 23, 2020

nice one, but video quality is low

创建者 SAID B

•

Mar 15, 2018

It's a very helpful course.

thanks

创建者 Vitaliy

•

Feb 28, 2018

Was nice but something is missing.

创建者 Lilith S

•

Nov 4, 2021

the code is not working sometimes

创建者 David B

•

Oct 5, 2017

W

e

e

k

3

e

x

e

r

c

i

c

e

c

o

u

l

d be improved

创建者 Julia W

•

Dec 18, 2023

Videos are of poor audio quality

创建者 Vincent L

•

Jul 16, 2020

Interesting and tough to finish.

创建者 Lenny F

•

Sep 28, 2019

Would like to have more practice

创建者 John M

•

Apr 4, 2019

TensorFlow needs more explaining

创建者 Sam M

•

Apr 28, 2018

Some errors in jupyter notebooks

创建者 ccbttn

•

Oct 8, 2017

last assignment need improvement

创建者 Julian F

•

Sep 30, 2017

A very practical hands-on study.

创建者 San Z

•

Jan 23, 2021

Tensorflow part is not that ok!