课程信息

149,416 次近期查看

学生职业成果

50%

完成这些课程后已开始新的职业生涯

36%

通过此课程获得实实在在的工作福利
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 3 门课程(共 7 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

Course requires strong background in calculus, linear algebra, probability theory and machine learning.

完成时间大约为32 小时
英语(English)
字幕:英语(English), 韩语

您将获得的技能

Bayesian OptimizationGaussian ProcessMarkov Chain Monte Carlo (MCMC)Variational Bayesian Methods

学生职业成果

50%

完成这些课程后已开始新的职业生涯

36%

通过此课程获得实实在在的工作福利
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 3 门课程(共 7 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

Course requires strong background in calculus, linear algebra, probability theory and machine learning.

完成时间大约为32 小时
英语(English)
字幕:英语(English), 韩语

提供方

国立高等经济大学 徽标

国立高等经济大学

教学大纲 - 您将从这门课程中学到什么

内容评分Thumbs Up83%(2,367 个评分)Info
1

1

完成时间为 2 小时

Introduction to Bayesian methods & Conjugate priors

完成时间为 2 小时
10 个视频 (总计 57 分钟), 2 个阅读材料, 2 个测验
10 个视频
Think bayesian & Statistics review7分钟
Bayesian approach to statistics5分钟
How to define a model3分钟
Example: thief & alarm11分钟
Linear regression10分钟
Analytical inference3分钟
Conjugate distributions2分钟
Example: Normal, precision5分钟
Example: Bernoulli4分钟
2 个阅读材料
About the University10分钟
MLE estimation of Gaussian mean10分钟
2 个练习
Introduction to Bayesian methods30分钟
Conjugate priors30分钟
2

2

完成时间为 7 小时

Expectation-Maximization algorithm

完成时间为 7 小时
17 个视频 (总计 168 分钟)
17 个视频
Probabilistic clustering6分钟
Gaussian Mixture Model10分钟
Training GMM10分钟
Example of GMM training10分钟
Jensen's inequality & Kullback Leibler divergence9分钟
Expectation-Maximization algorithm10分钟
E-step details12分钟
M-step details6分钟
Example: EM for discrete mixture, E-step10分钟
Example: EM for discrete mixture, M-step12分钟
Summary of Expectation Maximization6分钟
General EM for GMM12分钟
K-means from probabilistic perspective9分钟
K-means, M-step7分钟
Probabilistic PCA13分钟
EM for Probabilistic PCA7分钟
2 个练习
EM algorithm30分钟
Latent Variable Models and EM algorithm30分钟
3

3

完成时间为 2 小时

Variational Inference & Latent Dirichlet Allocation

完成时间为 2 小时
11 个视频 (总计 98 分钟)
11 个视频
Mean field approximation13分钟
Example: Ising model15分钟
Variational EM & Review5分钟
Topic modeling5分钟
Dirichlet distribution6分钟
Latent Dirichlet Allocation5分钟
LDA: E-step, theta11分钟
LDA: E-step, z8分钟
LDA: M-step & prediction13分钟
Extensions of LDA5分钟
2 个练习
Variational inference15分钟
Latent Dirichlet Allocation15分钟
4

4

完成时间为 6 小时

Markov chain Monte Carlo

完成时间为 6 小时
11 个视频 (总计 122 分钟)
11 个视频
Sampling from 1-d distributions13分钟
Markov Chains13分钟
Gibbs sampling12分钟
Example of Gibbs sampling7分钟
Metropolis-Hastings8分钟
Metropolis-Hastings: choosing the critic8分钟
Example of Metropolis-Hastings9分钟
Markov Chain Monte Carlo summary8分钟
MCMC for LDA15分钟
Bayesian Neural Networks11分钟
1 个练习
Markov Chain Monte Carlo30分钟

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关于 高级机器学习 专项课程

This specialization gives an introduction to deep learning, reinforcement learning, natural language understanding, computer vision and Bayesian methods. Top Kaggle machine learning practitioners and CERN scientists will share their experience of solving real-world problems and help you to fill the gaps between theory and practice. Upon completion of 7 courses you will be able to apply modern machine learning methods in enterprise and understand the caveats of real-world data and settings....
高级机器学习

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.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

  • If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.

  • Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.

  • Course requires strong background in calculus, linear algebra, probability theory and machine learning.

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