機械学習:Machine Learning General Machine Learning and Data Analysis
Overview of machine learning for beginners, differences between types of learning and results, no-free lunch theorem as a frame for machine learning.
人工知能:Artificial Intelligence
機械学習:Machine Learning python Clustering with R – k-means
Machine learning using R, unsupervised, non-hierarchical classification using k-means
R hierarchical clustering with R
Machine learning using R, classification with hierarchical clustering function hclust
R R Language Preferences
Overview of machine learning using R, setting up the environment and handling data
R Reference books on machine learning with R
Overview of machine learning with R, history of R and introduction to reference books
自然言語処理:Natural Language Processing Openrefine: Data cleansing tool
Overview of openrefine, a natural language processing tool used in DX and the Semantic Web
アルゴリズム:Algorithms Protected: Data Compression Algorithms(2)Lossy compression
Data Compression Algorithm Overview, Lossy Data Compression Algorithm, Exclusion Trick, Content Summary
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