Applied Machine Learning培训

课程编码

appliedml

课程时长

14 小时 通常来说是2天,包括中间休息。

课程概览

本培训课程面向希望在实际应用中应用Machine Learning人员。

听众

本课程适用于对统计学有一定了解并且知道如何编写R(或Python或其他选定语言)的数据科学家和统计学家。本课程的重点是数据/模型准备,执行,事后分析和可视化的实践方面。

目的是为有兴趣在工作中应用这些方法的参与者提供Machine Learning实际应用。

行业特定示例用于使培训与受众相关。

Machine Translated

课程大纲

  • Naive Bayes
  • Multinomial models
  • Bayesian categorical data analysis
  • Discriminant analysis
  • Linear regression
  • Logistic regression
  • GLM
  • EM Algorithm
  • Mixed Models
  • Additive Models
  • Classification
  • KNN
  • Bayesian Graphical Models
  • Factor Analysis (FA)
  • Principal Component Analysis (PCA)
  • Independent Component Analysis (ICA)
  • Support Vector Machines (SVM) for regression and classification
  • Boosting
  • Ensemble models
  • Neural networks
  • Hidden Markov Models (HMM)
  • Space State Models
  • Clustering

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