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A Few Things I Know About Her: A Personally Machine Learning Inspired Approach to Understand Surrounding Nature (Intelligent Systems Reference Library, Band 219) - Softcover

Apolloni, Bruno

 
9783030943813: A Few Things I Know About Her: A Personally Machine Learning Inspired Approach to Understand Surrounding Nature (Intelligent Systems Reference Library, Band 219)

Inhaltsangabe

This book reconsiders key issues, such as description and explanation, which affect data analytics.  For starters: the soul does not exist. Once released from this cumbersome roommate, we are left with complex biological systems: namely, ourselves, who must configure their environment in terms of worlds that are compatible with what they sense. Far from supplying yet another cosmogony, the book provides the cultivated reader with computational tools for describing and understanding data arising from his surroundings, such as climate parameters or stock market trends, even the win/defeat story of his son football team. Besides the superposition of the very many universes considered by quantum mechanics, we aim to manage families of worlds that may have generated those data through the key feature of their compatibility. Starting from a sharp engineering of ourselves in term of pairs consisting of genome plus a neuron ensemble, we toss this feature in different cognitive frameworks within a span of exploitations ranging from probability distributions to the latest implementations of machine learning. From the perspective of human society as an ensemble of the above pairs, the book also provides scientific tools for analyzing the benefits and drawbacks of the modern paradigm of the world as a service.

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Über die Autorin bzw. den Autor

Bruno Apolloni is Full Professor in Computer Science in the University of Milano, Italy. His main research interests are at the frontier area between probability and mathematical statistics and computer science, with special interest to pattern recognition and multivariate data analysis, probabilistic analysis of algorithms, subsymbolic and symbolic learning processes, and fuzzy systems. Witold Pedrycz is Professor and Canada Research Chair (CRC) in the Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada. He is also with the Systems Research Institute of the Polish Academy of Sciences. His dominant research is in Computational Intelligence, fuzzy modeling, knowledge discovery and data mining, pattern recognition, and knowledge-based neural networks. Dario Malchiodi is Assistant Professor in the Computer Science Department, University of Milano, Italy. His research activities concern the treatment of uncertain information and related aspects of mathematical statistics and artificial intelligence, including applications to machine learning and relevance learning. Simone Bassis is an assistant professor in the Department of Computer Science, University of Milano, Italy. His main research activities concern the inference of spatial and temporal processes, including linear and nonlinear statistical regression, fractal processes identification, and evolutionary dynamics.

Von der hinteren Coverseite

This book reconsiders key issues, such as description and explanation, which affect data analytics.  For starters: the soul does not exist. Once released from this cumbersome roommate, we are left with complex biological systems: namely, ourselves, who must configure their environment in terms of worlds that are compatible with what they sense. Far from supplying yet another cosmogony, the book provides the cultivated reader with computational tools for describing and understanding data arising from his surroundings, such as climate parameters or stock market trends, even the win/defeat story of his son football team. Besides the superposition of the very many universes considered by quantum mechanics, we aim to manage families of worlds that may have generated those data through the key feature of their compatibility. Starting from a sharp engineering of ourselves in term of pairs consisting of genome plus a neuron ensemble, we toss this feature in different cognitive frameworks within a span of exploitations ranging from probability distributions to the latest implementations of machine learning. From the perspective of human society as an ensemble of the above pairs, the book also provides scientific tools for analyzing the benefits and drawbacks of the modern paradigm of the world as a service.


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