神经网络与深度学习

本课程是深度学习专项课程专项课程的一部分

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103,071 个评分

Andrew Ng 另外 +2 位授课教师
顶尖授课教师

提供方

课程信息

In the first course of the Deep Learning Specialization, you will study the foundational concept of neural networks and deep learning. 
By the end, you will be familiar with the significant technological trends driving the rise of deep learning; build, train, and apply fully connected deep neural networks; implement efficient (vectorized) neural networks; identify key parameters in a neural network’s architecture; and apply deep learning to your own applications.

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.

学生职业成果

34%

完成这些课程后已开始新的职业生涯

33%

通过此课程获得实实在在的工作福利

11%

加薪或升职

可分享的证书

完成后获得证书

100% 在线

立即开始，按照自己的计划学习。

第 1 门课程（共 5 门）

深度学习专项课程

可灵活调整截止日期

根据您的日程表重置截止日期。

中级

Intermediate Python skills: basic programming, understanding of for loops, if/else statements, data structures
A basic grasp of linear algebra & ML

完成时间大约为20 小时

英语（English）

字幕：中文（繁体）, 阿拉伯语（Arabic）, 法语（French）, 乌克兰语, （欧洲人讲的）葡萄牙语, 中文（简体）, 意大利语, 巴西葡萄牙语, 越南语, 韩语, 德语（German）, 俄语（Russian）, 土耳其语（Turkish）, 英语（English）, 西班牙语（Spanish）, 日语

您将获得的技能

Deep LearningArtificial Neural NetworkBackpropagationPython ProgrammingNeural Network Architecture

学生职业成果

34%

完成这些课程后已开始新的职业生涯

33%

通过此课程获得实实在在的工作福利

11%

加薪或升职

可分享的证书

完成后获得证书

100% 在线

立即开始，按照自己的计划学习。

第 1 门课程（共 5 门）

深度学习专项课程

可灵活调整截止日期

根据您的日程表重置截止日期。

中级

Intermediate Python skills: basic programming, understanding of for loops, if/else statements, data structures
A basic grasp of linear algebra & ML

完成时间大约为20 小时

英语（English）

讲师

授课教师评分

4.91/5 （16,149 个评分）

提供方

deeplearning.ai

DeepLearning.AI is an education technology company that develops a global community of AI talent.

教学大纲 - 您将从这门课程中学到什么

内容评分97%（176,304 个评分）

周

周 1

完成时间为 2 小时

Introduction to deep learning

Be able to explain the major trends driving the rise of deep learning, and understand where and how it is applied today.

完成时间为 2 小时

7 个视频（总计 76 分钟）, 2 个阅读材料, 1 个测验

周

周 2

完成时间为 8 小时

Neural Networks Basics

Learn to set up a machine learning problem with a neural network mindset. Learn to use vectorization to speed up your models.

完成时间为 8 小时

19 个视频（总计 161 分钟）, 7 个阅读材料, 3 个测验

19 个视频

Binary Classification8分钟

Logistic Regression5分钟

Logistic Regression Cost Function8分钟

Gradient Descent11分钟

Derivatives7分钟

More Derivative Examples10分钟

Computation graph3分钟

Derivatives with a Computation Graph14分钟

Logistic Regression Gradient Descent6分钟

Gradient Descent on m Examples8分钟

Vectorization8分钟

More Vectorization Examples6分钟

Vectorizing Logistic Regression7分钟

Vectorizing Logistic Regression's Gradient Output9分钟

Broadcasting in Python11分钟

A note on python/numpy vectors6分钟

Quick tour of Jupyter/iPython Notebooks3分钟

Explanation of logistic regression cost function (optional)7分钟

Pieter Abbeel interview16分钟

7 个阅读材料

Clarification about Upcoming Logistic Regression Cost Function Video1分钟

Clarification about Upcoming Gradient Descent Video1分钟

Derivation of DL/dz (optional reading)10分钟

Copy of Clarification about Upcoming Logistic Regression Cost Function Video1分钟

Clarification of "dz"10分钟

Deep Learning Honor Code2分钟

Programming Assignment FAQ10分钟

1 个练习

Neural Network Basics30分钟

周

周 3

完成时间为 5 小时

Shallow neural networks

Learn to build a neural network with one hidden layer, using forward propagation and backpropagation.

完成时间为 5 小时

12 个视频（总计 109 分钟）, 2 个阅读材料, 2 个测验

12 个视频

Neural Networks Overview4分钟

Neural Network Representation5分钟

Computing a Neural Network's Output9分钟

Vectorizing across multiple examples9分钟

Explanation for Vectorized Implementation7分钟

Activation functions10分钟

Why do you need non-linear activation functions?5分钟

Derivatives of activation functions7分钟

Gradient descent for Neural Networks9分钟

Backpropagation intuition (optional)15分钟

Random Initialization7分钟

Ian Goodfellow interview14分钟

2 个阅读材料

Clarification: Activation Function1分钟

Clarification about Upcoming Backpropagation intuition (optional)1分钟

1 个练习

Shallow Neural Networks30分钟

周

周 4

完成时间为 5 小时

Deep Neural Networks

Understand the key computations underlying deep learning, use them to build and train deep neural networks, and apply it to computer vision.

完成时间为 5 小时

8 个视频（总计 64 分钟）, 3 个阅读材料, 3 个测验

8 个视频

Deep L-layer neural network5分钟

Forward Propagation in a Deep Network7分钟

Getting your matrix dimensions right11分钟

Why deep representations?10分钟

Building blocks of deep neural networks8分钟

Forward and Backward Propagation10分钟

Parameters vs Hyperparameters7分钟

What does this have to do with the brain?3分钟

3 个阅读材料

Clarification about Getting your matrix dimensions right video1分钟

Clarification about Upcoming Forward and Backward Propagation Video1分钟

Clarification about What does this have to do with the brain video1分钟

1 个练习

Key concepts on Deep Neural Networks30分钟

审阅

4.9

20621 条评论

5 stars
89.59%
4 stars
9.37%
3 stars
0.79%
2 stars
0.11%
1 star
0.11%

来自神经网络与深度学习的热门评论

由 MZ 提供Sep 12, 2018

This course is really great.The lectures are really easy to understand and grasp.The assignment instructions are really helpful and one does not need to know python before hand to complete the course.

由 JP 提供Feb 11, 2018

I would love some pointers to additional references for each video. Also, the instructor keeps saying that the math behind backprop is hard. What about an optional video with that? Otherwise, awesome!

由 JN 提供Feb 19, 2018

I know this is intended for a broad audience, but I found that the assignments were too easy. Not that they are testing easy material, but that the answers are almost stated directly in the questions.

由 NT 提供Jan 17, 2020

Very structured approach to developing a neural network which I believe I can use as foundation for any project regardless its complexity. Thanks professor Andrew Ng and the team for their dedication.

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关于深度学习专项课程

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.

In this Specialization, you will build neural network architectures such as Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, Transformers, and learn how to make them better with strategies such as Dropout, BatchNorm, Xavier/He initialization, and more. You will master these theoretical concepts and their industry applications using Python and TensorFlow. You will tackle real-world case studies such as autonomous driving, sign language reading, music generation, computer vision, speech recognition, and natural language processing. AI is transforming many industries. The Deep Learning Specialization 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. Along the way, you will get career advice from deep learning experts from industry and academia.

常见问题

我什么时候能够访问课程视频和作业？
讲座和作业的访问权限取决于您的注册类型。如果您以旁听模式参加课程，则可以免费查看大多数课程资料。要访问评分作业并获得证书，您需要在旁听期间或之后购买证书体验。如果看不到旁听选项：
课程可能不提供旁听选项。您可以尝试免费试用，也可以申请助学金。
课程可能会改为提供'完整课程，没有证书'。通过此选项，您可以查看所有课程材料、提交所要求的作业，以及获得最终成绩。这也意味着您将无法购买证书体验。
我订阅此专项课程后会得到什么？
您注册课程后，将有权访问专项课程中的所有课程，并且会在完成课程后获得证书。您的电子课程证书将添加到您的成就页中，您可以通过该页打印您的课程证书或将其添加到您的领英档案中。如果您只想阅读和查看课程内容，可以免费旁听课程。
Is financial aid available?
是的，Coursera 可以为无法承担费用的学生提供助学金。通过点击左侧“注册”按钮下的“助学金”链接可以申请助学金。您可以根据屏幕提示完成申请，申请获批后会收到通知。您需要针对专项课程中的每一门课程完成上述步骤，包括毕业项目。了解更多。
完成课程后，我会获得大学学分吗？
此课程不提供大学学分，但部分大学可能会选择接受课程证书作为学分。查看您的合作院校，了解详情。Coursera 上的在线学位和 Mastertrack™ 证书提供获得大学学分的机会。

还有其他问题吗？请访问学生帮助中心。

神经网络与深度学习

课程信息

学生职业成果

34%

33%

11%

您将获得的技能

学生职业成果

34%

33%

11%

讲师

Andrew Ng
顶尖授课教师

Kian Katanforoosh
顶尖授课教师

Younes Bensouda Mourri
顶尖授课教师

提供方

deeplearning.ai

教学大纲 - 您将从这门课程中学到什么

周 1

Introduction to deep learning

周 2

Neural Networks Basics

周 3

Shallow neural networks

周 4

Deep Neural Networks

审阅

来自神经网络与深度学习的热门评论

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神经网络与深度学习

课程信息

学生职业成果

34%

33%

11%

您将获得的技能

学生职业成果

34%

33%

11%

讲师

Andrew Ng顶尖授课教师

Kian Katanforoosh顶尖授课教师

Younes Bensouda Mourri顶尖授课教师

提供方

deeplearning.ai

教学大纲 - 您将从这门课程中学到什么

周 1

Introduction to deep learning

周 2

Neural Networks Basics

周 3

Shallow neural networks

周 4

Deep Neural Networks

审阅

来自神经网络与深度学习的热门评论

关于 深度学习 专项课程

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Coursera

社区

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Andrew Ng
顶尖授课教师

Kian Katanforoosh
顶尖授课教师

Younes Bensouda Mourri
顶尖授课教师

关于深度学习专项课程