R Reference books on machine learning with R
Overview of machine learning with R, history of R and introduction to reference books
機械学習:Machine Learning
R 機械学習:Machine Learning Protected: Bayesian Estimation and Information Theory
Bayesian estimation and information theory for artificial intelligence (AI), machine learning (ML), and natural language processing (NLP), from de Moivre's probability theory to Bayesian probability and Shannon's information engineering and tools for Bayesian estimation (STAN)
Clojure Sentence classification using liblinear and natural language processing
Classification in liblinear with Clojure, a natural language processing tool., liblinear, SVM, classification with Clojure
Clojure k-means and Clojure
Natural language processing tools, classification with k-means using Clojure, unsupervised learning
機械学習:Machine Learning Integration of probability and logic (1) Bayesian Net, KBMC, PRM and SRL
Integration of probability and logic, automatic generation of Bayesian nets using knowledge base (KBMC), prolog, backward reasoning
幾何学:Geometry Fundamentals of Computer Mathematics
Overview of computer mathematics as a basis for artificial intelligence and machine learning techniques, functions, sets, probability, simultaneous equations, differentiation, and integration.
哲学:philosophy The difference between causation and correlation
Consideration of causality and correlation as the basis for models of artificial intelligence and machine learning
アルゴリズム:Algorithms Protected: Pattern recognition algorithm
Introduction to pattern recognition algorithms, nearest neighbor methods, decision trees, and neural nets used in image processing and rule classification.