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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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63,489 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：

6876 - Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization 的 6900 个评论（共 7,283 个）

创建者 Tianxiang Z

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Nov 21, 2017

Great as usual except the typos in the assignment page

创建者 yashwanth v

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Jun 3, 2020

more introduction to tensorflow would be appreciated.

创建者 Clement K

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May 7, 2020

Very disapointed the course does not use tensorflow 2

创建者 Thomas P

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Mar 31, 2020

Some more basics on tensorflow would have been great!

创建者 Alexander S

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Mar 25, 2020

Very good overall, exercises could be a bit more free

创建者 Ritesh R A

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Dec 17, 2019

tensorflow sesssion should have been more descriptive

创建者 Mihaly K

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Nov 6, 2019

Assignments sometimes too easy, minimal input needed.

创建者 Brent D

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Feb 25, 2019

Tensorflow project was rushed and hard to understand.

创建者 Franklin W

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Jul 14, 2018

I want to be challenged more, less tips and more DIY.

创建者 Seth T

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Mar 26, 2018

Short course but was really excited to delve into TF.

创建者 王婷

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Feb 16, 2018

good PA examples, that could benefit my further study

创建者 Arhan G

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Jan 30, 2018

Andrew is a great lecturer. The videos are excellent.

创建者 Marko L

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Oct 6, 2025

would be nice to have the example of PyTorch as well

创建者 Alaa B

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Jun 13, 2023

very useful for both academic and business purposes

创建者 Nicolas M

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Jun 20, 2021

a little more practice on TF would have been nice...

创建者 Hak K C

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Apr 5, 2018

Course was concise and assignments were well guided.

创建者 Stu R

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Mar 11, 2018

Good course. Minor errors/typos in presented videos.

创建者 Venkatraman N

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Mar 10, 2018

Quite not challenging in the programming assignments

创建者 Uday Y

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Apr 29, 2020

Tensorflow assignment should be modified to use 2.x

创建者 Dmitry K

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Apr 14, 2020

TensorFlow should be updated to the latest version.

创建者 Fangshi L

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May 18, 2019

Good course, although some bugs in homework grading

创建者 Sumeet R

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Feb 10, 2019

very good course - gets to practical aspects of ML!

创建者 Juan O

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Dec 2, 2017

Having slides like in other courses will be helpful

创建者 SPS P

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Jun 27, 2020

Tensorflow could have been taught in a better way.

创建者 Sen C

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Dec 24, 2019

There should have been more exercise on tensorflow