Learning From Geospatial Data: Problems and Important Concepts of Machine Learning - Machine Learning Algorithms for Geospatial Data - Contents of the Book. Software Description - Short Review of the Literature - Exploratory Spatial Data Analysis: Presentation of Data and Case Studies: Exploratory Spatial Data Analysis - Data Pre-Processing - Spatial Correlations: Variography - Presentation of Data - k-Nearest Neighbours Algorithm: a Benchmark Model for Regression and Classification - Geostatistics: Spatial Predictions - Geostatistical Conditional Simulations - Spatial Classification - Software - Machine Learning Algorithms: Artificial Neural Networks: Introduction - Radial Basis Function Neural Networks - General Regression Neural Networks - Probabilistic Neural Networks - Self-Organising Maps - Gaussian Mixture Models And Mixture Density Network ? Support Vector Machines And Kernel Methods: Introduction to Statistical Learning Theory - Support Vector Classification - Spatial Data Classification with SVM - Support Vector Regression - Spatial Data Mapping with SVR - Advanced Topics in Kernel Methods.