This comprehensive book provides the readers with the core skills regarding data analysis and the application of algorithms. The book helps the readers establish a transition from equations to the source codes related to algorithms and from the interpretation of results to draw meaningful information about data within the real dataset and synthetic dataset. Specific applications of data analysis algorithms and detailed description of the main concepts for extracting knowledge from data are presented. In particular, the book shows how to use these algorithms for diagnosis and prediction in several medical fields, and for projections and forecasting in economy. The multidisciplinary approach includes data concerning algorithms, fractals, probability, statistics, image processing, medicine (neurology, radiology and psychiatry), and economy. Combining theory and application, this book intends to enhance knowledge and facilitate learning through the use of linear and multi linear models, decision trees, naive Bayesian classifier, support vector machines, k-Nearest Neighbour, artificial neural network algorithms as well as fractal and multifractal methods with Artificial Neural Networks (ANN). The intended audience of this book are undergraduates and postgraduate students, scholars, researchers and practitioners. Combines theory and applications in several fields.

Book jacket.