课程信息

82,758 次近期查看

学生职业成果

23%

完成这些课程后已开始新的职业生涯

22%

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 3 门)
可灵活调整截止日期
根据您的日程表重置截止日期。
高级
完成时间大约为63 小时
英语(English)
字幕:英语(English)

您将获得的技能

Bayesian NetworkGraphical ModelMarkov Random Field

学生职业成果

23%

完成这些课程后已开始新的职业生涯

22%

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 3 门)
可灵活调整截止日期
根据您的日程表重置截止日期。
高级
完成时间大约为63 小时
英语(English)
字幕:英语(English)

讲师

提供方

斯坦福大学 徽标

斯坦福大学

教学大纲 - 您将从这门课程中学到什么

内容评分Thumbs Up84%(3,527 个评分)Info
1

1

完成时间为 1 小时

Introduction and Overview

完成时间为 1 小时
4 个视频 (总计 35 分钟)
4 个视频
Welcome!3分钟
Overview and Motivation19分钟
Distributions4分钟
Factors6分钟
1 个练习
Basic Definitions8分钟
完成时间为 10 小时

Bayesian Network (Directed Models)

完成时间为 10 小时
15 个视频 (总计 190 分钟), 6 个阅读材料, 4 个测验
15 个视频
Reasoning Patterns9分钟
Flow of Probabilistic Influence14分钟
Conditional Independence12分钟
Independencies in Bayesian Networks18分钟
Naive Bayes9分钟
Application - Medical Diagnosis9分钟
Knowledge Engineering Example - SAMIAM14分钟
Basic Operations 13分钟
Moving Data Around 16分钟
Computing On Data 13分钟
Plotting Data 9分钟
Control Statements: for, while, if statements 12分钟
Vectorization 13分钟
Working on and Submitting Programming Exercises 3分钟
6 个阅读材料
Setting Up Your Programming Assignment Environment10分钟
Installing Octave/MATLAB on Windows10分钟
Installing Octave/MATLAB on Mac OS X (10.10 Yosemite and 10.9 Mavericks)10分钟
Installing Octave/MATLAB on Mac OS X (10.8 Mountain Lion and Earlier)10分钟
Installing Octave/MATLAB on GNU/Linux10分钟
More Octave/MATLAB resources10分钟
3 个练习
Bayesian Network Fundamentals6分钟
Bayesian Network Independencies10分钟
Octave/Matlab installation2分钟
2

2

完成时间为 1 小时

Template Models for Bayesian Networks

完成时间为 1 小时
4 个视频 (总计 66 分钟)
4 个视频
Temporal Models - DBNs23分钟
Temporal Models - HMMs12分钟
Plate Models20分钟
1 个练习
Template Models20分钟
完成时间为 11 小时

Structured CPDs for Bayesian Networks

完成时间为 11 小时
4 个视频 (总计 49 分钟)
4 个视频
Tree-Structured CPDs14分钟
Independence of Causal Influence13分钟
Continuous Variables13分钟
2 个练习
Structured CPDs8分钟
BNs for Genetic Inheritance PA Quiz22分钟
3

3

完成时间为 17 小时

Markov Networks (Undirected Models)

完成时间为 17 小时
7 个视频 (总计 106 分钟)
7 个视频
General Gibbs Distribution15分钟
Conditional Random Fields22分钟
Independencies in Markov Networks4分钟
I-maps and perfect maps20分钟
Log-Linear Models22分钟
Shared Features in Log-Linear Models8分钟
2 个练习
Markov Networks8分钟
Independencies Revisited6分钟
4

4

完成时间为 21 小时

Decision Making

完成时间为 21 小时
3 个视频 (总计 61 分钟)
3 个视频
Utility Functions18分钟
Value of Perfect Information17分钟
2 个练习
Decision Theory8分钟
Decision Making PA Quiz18分钟

审阅

来自PROBABILISTIC GRAPHICAL MODELS 1: REPRESENTATION的热门评论

查看所有评论

关于 概率图模型 专项课程

Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that interact with each other. These representations sit at the intersection of statistics and computer science, relying on concepts from probability theory, graph algorithms, machine learning, and more. They are the basis for the state-of-the-art methods in a wide variety of applications, such as medical diagnosis, image understanding, speech recognition, natural language processing, and many, many more. They are also a foundational tool in formulating many machine learning problems....
概率图模型

常见问题

  • Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

    • The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
    • The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
  • 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。

  • 如果订阅,您可以获得 7 天免费试听,在此期间,您可以取消课程,无需支付任何罚金。在此之后,我们不会退款,但您可以随时取消订阅。请阅读我们完整的退款政策

  • 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

  • Apply the basic process of representing a scenario as a Bayesian network or a Markov network

    Analyze the independence properties implied by a PGM, and determine whether they are a good match for your distribution

    Decide which family of PGMs is more appropriate for your task

    Utilize extra structure in the local distribution for a Bayesian network to allow for a more compact representation, including tree-structured CPDs, logistic CPDs, and linear Gaussian CPDs

    Represent a Markov network in terms of features, via a log-linear model

    Encode temporal models as a Hidden Markov Model (HMM) or as a Dynamic Bayesian Network (DBN)

    Encode domains with repeating structure via a plate model

    Represent a decision making problem as an influence diagram, and be able to use that model to compute optimal decision strategies and information gathering strategies

    Honors track learners will be able to apply these ideas for complex, real-world problems

还有其他问题吗?请访问 学生帮助中心