Protected: Graphical Models Overview and Markov Probability Fields
Graphical model overview for efficient approach to stochastic generative models, Markov stochastic processes
Protected: An overview of the expert integration problem in online forecasting and its implementation in Regret
Overview of online predictive learning for solving sequential prediction problems, introduction to Regret
Protected: Continuous Optimization in Machine Learning – Overview
Explanation of the mathematical theory underlying optimization algorithms for machine learning.
Protected: Reinforcement Learning Overview
An overview of reinforcement learning for learning sequential decision rules
Protected: Nonparametric Bayesian Point Processes and the Mathematics of Statistical Machine Learning Overview
An overview of the nonparametric Bayesian method, a probability generation model in infinite dimensions
Protected: Decision Tree Algorithm (4) Rule Classification using R
Rule extraction with R using decision tree algorithm, C5.0, and Ripper
Protected: Decision Tree Algorithm (2) Clustering with R
Classification using R, a classical machine learning algorithm, the decision tree algorithm.
Protected: Decision Tree Algorithm (3) Rule Classification Overview
Rule extraction using the decision tree algorithm, a classical machine learning algorithm.
Protected: Decision Tree Algorithm (1) Overview
Overview of the decision tree algorithm, a classical machine learning algorithm.
Protected: Introduction to Machine Learning with Bayesian Inference
An overview of machine learning with Bayesian inference, a probabilistic generative model.