Course Outline

  • 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
  14 Hours
 

Number of participants


Starts

Ends


Dates are subject to availability and take place between 09:30 and 16:30.
Open Training Courses require 5+ participants.

Related Courses

Related Categories