This ApressOpen book Efficient Learning Machines: Theories, Concepts, and Applications for Engineers and System Designers explores the major topics of machine learning, including knowledge discovery, classifications, genetic algorithms, neural networking, kernel methods, and biologically-inspired techniques.
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Computer Vision Metrics: Survey, Taxonomy, and Analysis provides an extensive survey and analysis of current and historical feature description and machine vision methods, with a detailed taxonomy for local, regional and global features. The taxonomy includes search methods, spectra components, descriptor representation, shape, distance functions, accuracy, efficiency, robustness and invariance attributes, and more.
The fundamental algorithms in data mining and analysis are the basis for business intelligence and analytics, as well as automated methods to analyze patterns and models for all kinds of data. Data Mining and Analysis: Fundamental Concepts and Algorithms, a textbook for senior undergraduate and graduate data mining courses provides a comprehensive overview from an algorithmic perspective, integrating concepts from machine learning and statistics, with plenty of examples and exercises.
During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework.
Neural networks are a bio-inspired mechanism of data processing, that enables computers to learn technically similar to a brain and even generalize once solutions to enough problem instances are tought. The manuscript “A Brief Introduction to Neural Networks” is divided into several parts, that are again split to chapters.
Learning and Intelligent Optimization (LION) is the combination of learning from data and optimization applied to solve complex and dynamic problems. The LION way is about increasing the automation level and connecting data directly to decisions and actions. Download the entire book or individual chapters in pdf format.
A Course in Machine Learning is an introductory book that covers most major aspects of modern machine learning.
“AI Algorithms, Data Structures, and Idioms in Prolog, Lisp, and Java”, by George F. Luger and William A. Stubblefield, is available in pdf format.
Full PDF book of “Computer Vision: Models, Learning, and Inference” by Simon J.D. Prince is available for free. It is primarily meant for advanced undergraduate and graduate students, the detailed methodological presentation will also be useful for practitioners of computer vision.
“The Quest for Artificial Intelligence: A History of Ideas and Achievements”, written by Nils J. Nilsson is free to download. The entire 707 page book is available in pdf format.