Pattern Recognition培训

课程编码

datamodeling

课程时长

21 小时 通常来说是3天,包括中间休息。

要求

  • Understanding of statistics.
  • Familiarity with multivariate calculus and basic linear algebra.
  • Some experience with probabilities.

Audience

  • Data analysts
  • PhD students, researchers and practitioners

课程概览

该讲师指导的实时课程介绍了模式识别和机器学习领域。它涉及统计学,计算机科学,信号处理,计算机视觉,数据挖掘和生物信息学的实际应用。

该课程是互动的,包括大量的动手练习,教师反馈,以及获得的知识和技能测试。

Machine Translated

课程大纲

Introduction

Probability Theory, Model Selection, Decision and Information Theory

Probability Distributions

Linear Models for Regression and Classification

Neural Networks

Kernel Methods

Sparse Kernel Machines

Graphical Models

Mixture Models and EM

Approximate Inference

Sampling Methods

Continuous Latent Variables

Sequential Data

Combining Models

Summary and Conclusion

客户评论

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