datamodeling
21 小时 通常来说是3天，包括中间休息。
Audience
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
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
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.jpg "european organization for nuclear research (cern)")
.jpg "international air transport association (iata)")
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