Читать книгу Informatics and Machine Learning. From Martingales to Metaheuristics онлайн

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In this text I provide a background on various methods from Informatics and Machine Learning (ML) that together comprise a “complete toolset” for doing data analytics work at all levels – from a first year undergraduate introductory level to advanced topics in subsections suitable for graduate students seeking a deeper understanding (or a more detailed example). Numerous prior book, journal, and patent publications by the author are drawn upon extensively throughout the text [1–68]. Part of the objective of this book is to bring these examples together and demonstrate their combined use in typical signal processing situations. Numerous other journal and patent publications by the author [69–100] provide related material, but are not directly drawn upon this text. The application domain is practically everything in the digital domain, as mentioned above, but in this text the focus will be on core methodologies with specific application in informatics, bioinformatics, and cheminformatics (nanopore detection, in particular). Other disciplines can also be analyzed with informatics tools. Basic questions about human origins (anthrogenomics) and behavior (econometrics) can also be explored with informatics‐based pattern recognition methods, with a huge impact on new research directions in anthropology, sociology, political science, economics, and psychology. The complete toolset of statistical learning tools can be used in any of these domains.