datamodeling
21 時間： 同常來說包括休息是 3天
Audience
該講師指導的實時課程介紹了模式識別和機器學習領域。它涉及統計學，計算機科學，信號處理，計算機視覺，數據挖掘和生物信息學的實際應用。
該課程是互動的，包括大量的動手練習，教師反饋，以及獲得的知識和技能測試。
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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